Label Free Biosensors and Cells

ABSTRACT

Disclosed are compositions and methods for using label free optical biosensors for performing cell assays. In certain embodiments the assays can be performed in high throughput methods and can be multiplexed.

I. CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application Ser.No. 60/668,908 filed on Apr. 5, 2005 and entitled “Label Free Biosensorsand Cells” which is incorporated by reference herein.

II. BACKGROUND

The drug discovery and development process that ultimately brings newdrugs to market is a complex and costly process. Traditionally, theearly stages of drug discovery utilized affinity binding assays thatgenerally were done in vitro and provided limited information on theability of a potential drug compound to illicit the effect on the targetof interest. Many of these potential leads fail when tested either incell-based assays or animal model-based validation assays at thepreclinical/clinical trials, resulting in high attrition rates. Morerecently, innovative cell-based technologies including high-contentscreening technologies have gained popularity in the pharmaceutical andbiotech industries. These assay technologies provide functional, kineticcell-based information on the cellular consequences of target-compoundinteraction. The data obtained include information on signaltransduction pathways, drug mechanisms of action, efficacy, selectivityand cytotoxicity. Most of the existing cell-based technologies thatrequire the use of fluorescent labels or luminescence labels forimaging-based detection are generally focused on evaluating discreteintracellular events (e.g., Ca²⁺ flux, cAMP generation and accumulation,target translocation, reporter gene generation, etc). Because of thecomplexity of cell function, cellular responses generally result fromintegration of multitude signals, and thus assay technologies based on agiven single-cellular response or signal tend to fail to generateinformation regarding the overall integrated cellular response to drugstimulation. The use of labels or the use of artificial enhancements(e.g., transfection or RNAi knockout) or the use of a reporter genesystem, for example, could contribute in an adverse way to elucidatingthe real cellular physiology of the target of interest. For thesereasons, there is a continuing need for being able to assay the effectof molecules on living cells, such as assaying whether the moleculeeffects a particular signaling pathway, such as a G protein coupledreceptor (GPCR) or epidermal growth factor receptor (EGFR), or whetherthe molecule causes the cell to proliferate or causes the cell to die orstop growing. The use of label free or label independent detection (LID)biosensors is desirable because the biosensors bypass the need for oftencomplex labeling strategies and detection mechanisms. Label freebiosensors are more convenient for high through put methods. Disclosedare methods and systems for using label free biosensors to perform anytype of cell assay, including assaying signal transduction pathways andcell proliferation and death.

III. SUMMARY

Disclosed are methods and compositions related to label free biosensorsand their uses with cells.

IV. BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate several embodiments and togetherwith the description illustrate the disclosed compositions and methods.

FIG. 1 shows an example of a specific detection scheme of an opticalwaveguide grating (OWG) microplate after live cells become adherent onthe sensor surface. The image showed a resonant band image of 5 columnsof 7 sensors after cell culture with a cell confluency of ˜95% obtainedusing an arrayed angular interrogation system. The arrayed angularinterrogation system consists of a launch system for generating an arrayof light beams such that each illuminates an OWG sensor and a receivingsystem for receiving all responses from the light beams reflected fromthese sensors. This system allows simultaneously measuring responses ofadherent cells from multiplex systems. This example is for a 5×7, butone can utilize a 6×7, or 7×7, or any configuration that fits with thelight generation and receiving systems. These measurements can be takenin real time with a time resolution of ˜3 sec, for example. The brokencircle indicates that the cell density is not even across this sensor,as confirmed by light microscopic imaging.

FIG. 2 a shows optical biosensors for cell assays based onstimulation-induced directional mass redistribution within adherentlayer of cells. The example shown is an optical waveguide gratingsensor, consisting of a thin film of Nb₂O₅ with a high refractive index(n_(F)=2.36) and a thickness of d_(F) (75 nm) on a glass substrate of anindex of n_(s)=1.50, an adlayer of cells on the waveguide film with anoverall refractive index of n_(A)=1.37, and a surrounding medium with anindex of ˜1.33 (n_(c)). The OWG biosensor is an evanescent-wave sensor,based on the resonant coupling of light into a waveguide by means of adiffraction grating. A laser illuminates the waveguide at varying anglesand light is coupled into the waveguide only at specific angles,determined by the effective refractive index (A) of a guided mode.Ligand-induced target activation leads to recruitment oftarget-interacting component(s) to the target, movement of the resultedtarget complexes, and potentially the remodeling of cell cytoskeletonstructure (i.e., morphological changes). When such movements or changesoccur in the very periphery of an OWG sensor surface on which the cellsare cultured, a DMR signal, as indicated by the arrow, is generated atcertain time and can be monitored in real time. The ligand-induceddirectional mass redistribution within adherent cell layer leads to achange in effective refractive index, which, in turn, results in angleshift of the out-coupled light. FIG. 2 b A three-layer configuration fordetecting the stimulation-mediated vertical mass redistribution withinthe sensing volume. The bottom portion of cells is viewed to consist ofmultiple equal-spaced and homogenous thin layers, each layer has its ownrefractive index n_(i), protein concentration C_(i), distance Z_(i)(away from the sensor surface). A grating with a periodicity of Λ isembedded with the waveguide film with a refractive index of n_(F) and athickness of d_(F). The waveguide film is deposited on the top surfaceof a substrate with a refractive index of n_(s).

FIG. 3 The phase shift as a function of asymmetrically lateralredistribution of cellular contents mediated by stimulation. The guidedlight, propagating in the planar waveguide, is viewed as zigzag waves.The inhomogeneity of lateral mass distribution within the sensing volumeresults in broadening, and even splitting of the resonant peak of agiven mode.

FIG. 4 shows the intensity of the evanescent wave of a guided mode ofthe sensor as a function of distance away from the sensor surface.

FIG. 5 shows an alternative symmetry of OWG sensors. In this so-calledreverse symmetry waveguide configuration, it consists of a waveguidefilm (e.g., Nb₂O₅) supported by typically a 1-100 micron thick layer ofnanoporous silica with or without a glass bottom support. The nanoporoussilica has an effective refractive index of ˜1.1 and the refractiveindex of the silica is lower than the refractive index of the covermedium, which are generally aqueous solution for our applications in thepresent invention.

FIG. 6 shows parameters on which cell assays can be based using an OWGbiosensor. Shown in 6A is a typical time-dependent response of anadherent layer of exemplary quiescent A431 cells of ˜95% confluencyinduced by 8 nM EGF, as obtained using the angular interrogation system.As shown in the graph of 6A, six parameters that can define the kineticsof the stimulation-induced directional mass redistribution within thecells are 1) overall dynamics (i.e., shape), 2) phases of the response(e.g., in this specific example, there are three phases:Positive-Directional Mass Redistribution (P-DMR), net-zero DirectionalMass Redistribution (net-zero DMR) and Negative-Directional MassRedistribution (N-DMR)), 3) kinetics of each phases, 4) total durationtime of both P- and N-DMR phases, 5) total amplitudes of both P- andN-DMR phases, and 6) transition time τ from the P— to N-DMR phase. FIG.6B shows a typical resonant peak, obtained using TM₀ mode, of exemplaryA431 cells of ˜90% confluency and illustrates four additionalparameters: 7) peak position, 8) intensity, 9) shape and 10) width athalf maximum (PWHM). FIG. 6C shows a typical TM₀ resonant band image ofa biosensor with biosensors, a biosensor #5, on which exemplary A431cells were cultured with a confluency of ˜95%. The data was obtainedusing an arrayed angular interrogation system and illustrates 5 fiveadditional features: 11) band shape, 12) position, 13) intensity, 14)distribution and 15) width. All of these parameters can be usedindependently or together for any given application of any cell assaysusing biosensors as disclosed herein. The use of the parameters in anysubset or combination can produce a signature for a given assay or givenvariation on a particular assay, such as a signature for a cell receptorassay, such as a specific signature for an EGF receptor based assay.

FIG. 7 shows dose dependent responses of quiescent A431 cells induced byEGF. (A) Real time kinetics, obtained in parallel using our system, ofthe cell responses induced by different concentrations of EGF. The finalconcentrations of EGF are indicated in the graph. (B) The amplitudes ofthe N-DMR signals, calculated based on the difference between thetransition phase and the end phase as indicated in FIG. 7A, as afunction of EGF concentration. A typical saturation curve was obtained.(C) The time r for the transition from the P-DMR to the N-DMR event as afunction of EGF concentration. (D) The value of κ, obtained usingnon-linear regression, of the N-DMR event was plotted as a function ofEGF concentration.

FIG. 8 shows a method for screening and classifying compounds against aparticular target or signaling pathway based on directional massredistribution. In this figure, a marker can be an activator ordeactivator of a particular target or signaling pathway or function ofthe cell that leads to or prevents a directional mass redistributionevent or signal. The broken arrow indicates that the two steps can beinterchangeable or combined together. Both steps 804 and 806 can beconsidered a stimulatory event as discussed herein.

FIG. 9 shows a schamtic drawing of a biological cell with varioustypical components. The cell consists of a cytoplasm (typically 10-30μM) containing numerous organelles. The largest organelle is thenucleus, whose size ranges typically between 3 and 10 g/m. The nucleusis filled with proteins, the most important one being chromatin.Mitochondria are small organelles comprised of a series of foldedmembranes with sizes typically ranging from 0.5-1.5 μm. Other cellcomponents include endoplasmic reticulum (ER) (typically 0.2-1 μm),lysomes (typically 0.2-0.5 μm), peroxisomes (typically 0.2-0.5 μm), andendosomes (typically ˜100 μm).

FIG. 10 shows a diagram showing an optical LID system being used tomonitor a mass redistribution (e.g. GPCR translocation) within a livingcell in accordance with methods and systems disclosed herein.

FIG. 11 shows the evanescent field (i.e, relative response) as afunction of distance of a biological target away from the sensor surfacefor three types of sensors which have three distinct penetration depths:100, 200, and 300 nm, respectively. This demonstrates the importance ofvariable penetration depths for cell sensing, especially for probingmovements or a DMR event inside the cells.

FIG. 12 shows a method for target identification and evaluation based ondirectional mass redistribution. Note: (1) a marker in this situation isan activator or deactivator of a particular target that leads to orprevents a directional mass redistribution event or signal, (2) Theresponses obtained can be used to identify the level of the target inthe specific cells, or evaluate the target in a particular signalingpathway or a given type of disease cells, and (3) 1206 could beconsidered a stimulatory event as disclosed herein.

FIG. 13 shows an alternative method for target identification andevaluation based on directional mass redistribution. Note: (1) a markerin this situation is an activator or deactivator of a particular targetthat leads to or prevent a directional mass redistribution event orsignal, (2) The responses obtained can be used to identify the level ofthe target in the specific cells, or evaluate the target in a particularsignaling pathway or a given type of disease cells, and (3) both 1303and 1304 could be considered a stimulatory event as disclosed herein.

FIG. 14 shows an optical LID biosensor microplate that can be used, forexample, in the alternative method showed in FIG. 13. This particularmicroplate is a multi-compartment plate and has an opticalbiosensor-embedded multi-compartment within each well. In this 96 wellmicroplate, each well contains four compartments; each compartment hasone waveguide grating substrate embedded, and can be used to host asingle type of cells or a target of interest. The four compartments areseparated by inner walls, the height of the inner walls (preferablybetween 100 microns and 2 millimeters) is much lower than those of eachwell (which is typical the height of any given microplate), such thateach well having four compartments can be used to examine simultaneouslythe effect of one drug candidate on multiple targets or multiple typesof cells, whatever different target may be in each compartment. The graylines represent a wavegude grating-based biosensor.

FIG. 15 shows an alternative method for target identification andevaluation based on directional mass redistribution. Note: (1) a markerin this situation is an activator or deactivator of a particular targetthat leads to or prevents a directional mass redistribution event orsignal, (2) The responses obtained can be used to identify the level ofthe target in the specific cells, or evaluate the target in a particularsignaling pathway or a given type of disease cells, and (3) 1503, 1504,1508, and 1509 can be considered stimulatory events as disclosed herein.

FIG. 16 shows a diagram that shows the different states associated withcell modulation by a stimulatory event, such as the GPCR translocationwithin the living cell that can be identified by analyzing the timedependent optical response output from an optical LID system, forexample, like that shown in FIG. 10.

FIG. 17 shows a flowchart illustrating the basic steps of a method formonitoring in real time a stimulatory event, such as an agonist-inducedmass redistribution of a cell receptor, including GPCR translocationwithin living cells, using an optical LID biosensor as disclosed herein.1706 and 1708 can be considered stimulatory events as disclosed herein.

FIG. 18 shows an example of target identification based on directionalmass redistribution. Note: (1) The example shown in this graph isEGF-induced DMR responses of a cancel cell line A431 in comparison withanother cell line CHO; (2) EGF-induced DMR responses of an adherentlayer of A431 cells of ˜95% confluency cultured under three differentconditions as indicated in the figure were compared with that of anadlayer of Chinese hamster ovary cells of ˜95% confluency cultured in0.1% fetal bovine serum (FBS) for 20 hours. Before addition of 50 μl 4×solution of EGF (32 nM), the cells covered by 100 μl the medium weresubject to treatment with 25 μl regular Hank's balanced salt solution(HBSS) at least twice, separated by 15 minutes such that the cells reacha steady state, as indicated by a prolonged net-zero response; (3) Thestimulatory event is an activator (i.e., cognate ligand, EGF) of aparticular target (EGFR) that leads to a directional mass redistributionevent or signal; and (4) The A431 cell endogenously over-expressesepidermal growth factor receptor (EGFR) (˜1,700,000 copies per cell). Incontrast, the CHO does not endogenously express EGFR. 1801 representsthe output data for the CHO cells. 1802 represents the output data forA431 cells in 0.1% fetal calf serum (FCS) for 20 hours. 1803 representsthe output data for A431 cells in 10% FCS. 1804 represents the outputdata for A431 cells in 0.1% FCS for 4 hours.

FIG. 19 shows a flowchart illustrating the basic steps of a method forscreening a stimulatory event, such as an agonist event, against atarget, such as a GPCR, based on mass redistribution within living cellsusing an optical LID biosensor as disclosed herein.

FIG. 20 shows a flowchart illustrating the basic steps of a method forscreening a stimulatory event, such as an antagonist event, against atarget of a cell, such as a receptor, such as a GPCR, based on massredistribution within living cells using an optical LID biosensor asdisclosed herein. 2006 and 2008 can be considered stimulatory events asdisclosed herein.

FIG. 21 shows a flowchart illustrating the basic steps of a method forcreating a self-referencing optical LID biosensor that can be used inany one of the methods disclosed herein.

FIG. 22 shows a flowchart illustrating the basic steps of another methodfor creating a self-referencing optical LID biosensor that hosts twotypes of cells adherent at spatially separated regions within the samesensor and which can be used in any one of the methods disclosed herein.2212 can be considered a stimulatory event as disclosed herein.

FIG. 23 shows a flowchart illustrating the basic steps of a method formonitoring a stimulatory event, such as an agonist-induced receptorevent, such as a GPCR receptor, via mass redistribution within multipletypes of living cells using an optical LID biosensor as disclosedherein. 2308 can be considered a stimulatory event as disclosed herein.

FIG. 24 shows a flowchart illustrating the basic steps of a method forscreening a panel of compounds, such as potential agonists orantagonists for a particular receptor, such as against multiple GPCRswithin a single type of living cell based on mass redistribution usingan optical LID biosensor as disclosed herein. 2406 and 2408 can beconsidered a stimulatory event.

FIG. 25 shows a method to screen modulators that interfere withcytoskeleton structures of cells. 2506, 2508, and 2510 can be considereda stimulatory event.

FIG. 26 shows an example of a method to screen modulators that interferewith cholesterol effluxing. 2606, 2608, and 2610 can be considered astimulatory event.

FIG. 27 shows a schematic drawing showing the lipid signaling andtransport in the body.

FIG. 28(A) shows time-dependent responses of methyl-beta-cyclodextrin(mβCD) on adlayer of quiescent A431 cells or HeLa cells on LID sensors.FIG. 28(B) shows the effect of compound (20 nM EGF or 1000 nM H7) onmβCD-induced responses of quiescent A431 cells. The quiescent A431 cellswere pretreated with corresponding compound for at least 40 minutesbefore introduction of mβCD solution.

FIG. 29 shows a DMSO-induced dose-response and time-dependent responseof a CHO cell layer adherent on a waveguide based biosensor. At 20%DMSO, four events are observed: (A) large response signal due to thebulk index change right after the introduction of DMSO solution; (B) asmall decreased signal probably due to the mixing of the two fluids inthe well; (C) a slow and steady increased signal probably because DMSOpenetrates and replaces the biofluid inside the cells; and (D) a prolongdecreased signal due to the loss of proteins or other biologicalmolecules of cells caused by the toxicity of high concentration of DMSO.

FIG. 30 shows a DMSO-induced dose-response and time-dependent responseof A431 cell layer adherent on a wave-guide based biosensor. Theresponses observed were similar to those on CHO cell layers.

FIG. 31A shows the intensity of the incoupled light as a function of theincident angle for a layer of CHO cells with different confluencies(30%, 50% and 90%) cultured on a Nb₂O₅-based optical waveguidebiosensors. The coupling mode is transverse magnetic (TM₀) mode. FIG.31B The width of the peak at half-maximum (PWHM) using TM₀ mode iscalculated and plotted as a function of CHO cell confluency.

FIG. 32A and FIG. 32B shows the TM₀ mode resonant peaks of a layer ofCHO cells with two different confluencies, 5% and 75%, respectively,cultured on waveguide grating sensors. FIG. 32B the resonant peakspectra were recorded at different times after addition of DMSO (with afinal concentration of 18%). The broken arrow in the right graph showsthe broadening and splitting of the resonance peak at the time of 25 minafter DMSO treatment.

FIG. 33 shows a TM₀ mode resonance band image of the whole sensors, eachsensor was covered by a layer of CHO cells at different confluencies (asindicated in the Figure). The images are taken after 25 min treatmentwith buffer (column 2), and with 18% DMSO (column 1).

FIG. 34 shows a TM₀ mode resonance band image of the whole sensors, eachsensor was covered by a layer of CHO cells at same confluency (˜95%).The images are taken after a 25 min treatment with buffer (column 2),and with different concentrations of DMSO (column 1, and column 3, asindicated in the Figure). The circles indicate the peak splittinginduced by the toxicity of DMSO of ˜15% on CHO cells.

FIG. 35A and FIG. 35B show phase contrast images of CHO cells culturedon a waveguide grating sensor area and outside the sensor area,respectively.

FIG. 36A shows the intensity of the incoupled light of the TM₀ mode as afunction of the incident angle for CHO cells after cultured onNb₂O₅-based optical waveguide biosensors for 36 hours. Different initialseeding numbers of cells are used to study the proliferation rate of CHOcells. The coupling mode is transverse magnetic (TM₀) mode. FIG. 36Bshows that the width of the peak at half-maimum (PWHM) using TM₀ mode iscalculated and plotted as a function of initial seeding numbers of CHOcells.

FIG. 37 shows a monitoring of CHO cells proliferation at differentinitial cell seeding numbers on the waveguide grating biosensors. Theshape and position of the TM₀ mode resonance images of the whole sensorsis observed to be dependent on initial seeding cell numbers, indicatingthat the proliferation rate of CHO cells depends on initial seeding cellnumbers.

FIG. 38 shows epidermal growth factor receptor (EGFR) signalingpathways. The epidermal growth factor (EGF) family of receptor tyrosinekinases consists of four receptors, EGF-R (ErbB1), ErbB2 (Neu), ErbB3,and ErbB4. Members of the EGFR family contain a cytoplasmic tyrosinekinase domain, a single transmembrane domain, and an extracellulardomain that is involved in ligand binding and receptor dimerization.Binding of ligand to EGFR leads to formation of homodimers orheterodimers of the receptor with other family members. Each dimericreceptor complex will initiate a distinct signaling pathway byrecruiting different Src homology 2 (SH2)-containing effector proteins.Dimerization results in autophyosphorylation initiating a diverse arrayof downstream cellular signaling pathways. The activated EGF-R dimercomplexes with the adapter protein, Grb, coupled to the guaninenucleotide releasing factor, SOS. The Grb-SOS complex can either binddirectly to phosphotyrosine sites in the receptor or indirectly throughShc. These protein interactions bring SOS in close proximity to Ras,allowing for Ras activation. This subsequently activates the ERK and JNKsignaling pathways that, in turn, activate transcription factors, suchas c-fos, AP-1, and Elk-1, that promote gene expression and contributeto cell proliferation. EGF=epidermal growth factor, EGFR epidermalgrowth factor receptor, Shc=src homology domain consensus, grb2=growthfactor receptor-bound protein 2, SOS=mammalian son of sevenless, Raf Rasactivated factor, MEK=MAP kinase kinase, MAPK=mitogen activated proteinkinase, PI3K=phosphatidylinositol 3′ kinase, PIP2=phosphatidyl inositol3,4-diphosphate, PIP3=phosphatidyl inositol 3,4,5 triphosphate,PLCγ=phospholipase—γ, DAG=diacyl glycerol, IP3=inositol 3,4,5triphosphate, PKC=protein kinase C.

FIG. 39 shows the net responses of the P-DMR and N-DMR events observedfor the EGF-induced responses of proliferating (indicated as A431) andquiescent A431 cells (indicated as A431-S), in comparison with quiescentCHO cells (indicated as CHO).

FIG. 40 shows the effect of a 30-minute pretreatment of a layer ofstarved A431 cells with different compounds on the time-dependentresponse after the addition of 16 nM EGF. The final concentrations ofthe compounds are 0.5 μg/ml, 0.1 mM, 1 μM, 0.1 μM, and 50 μM for growthhormone (GH), PD98059, PP1, wortinannin, and dynamin inhibitory peptide(DIP), respectively.

FIG. 41 shows the net responses of the P-DMR and N-DMR signals for alayer of starved A431 cells, cultured on waveguide biosensors, inresponse to stimulation with 16 nM EGF.

FIG. 42 shows a dose dependent suppression of the EGF-induced responsesof quiescent A431 cells induced by AG1478. (A) Pretreatment of quiescentA431 cells with different concentrations of AG1478 led to a dosedependent alternation of the response induced by 32 nM EGF. (B) Theamplitudes of the N-DMR signals as a function of AG1478 concentration.

FIG. 43 shows the effect of a Src kinase inhibitor PP1 on theEGF-induced DMR response of quiescent A431 cells.

FIG. 44 shows the effect of Ras/MAPK pathway modulators on 32 nMEGF-induced response of the quiescent A431 cells.

FIG. 45 shows the effect of protein kinase inhibitors on 32 nMEGF-induced response of the quiescent A431 cells.

FIG. 46 shows the effect of cytoskeleton modulators on 32 nM EGF-inducedresponse of the quiescent A431 cells.

FIG. 47 shows the effect of phosphodiesterase and other inhibitors on 32nM EGF-induced response of the quiescent A431 cells.

FIG. 48 shows two major contributors to the overall DMR signal inducedby EGF of quiescent A431 cells observed using the optical biosensor. EGFinduced EGFR internalization, cell morphology changes, and directionalmass redistribution in A431 cells at room temperature (22° C.). (A)Fluorescence image of proliferating A431 (10% FBS) after staining with 8nM tetramethylrhodamine labeled EGF (TMR-EGF) and sequent stripped awaythe surface-bound TMR-EGF with an acidic solution at 4° C. (B)Fluorescence image of quiescent A431 (0.1% FBS) after staining withTMR-EGF. (C) Fluorescence image of quiescent A431 (0.1% FBS) afterstaining and sequent stripped away the surface-bound TMR-EGF with anacidic solution at 4° C. (D) Quiescent A431 cells treated with 16 nM EGFfor the indicated times were examined using fluorescence microscopy witha 32× magnification after fixation and stained with Texas red-labeledphalloidin.

FIG. 49 shows a schematic drawing of one possible mechanism forEGF-induced DMR signals—receptor endocytosis.

FIG. 50 shows dose dependent responses of Chinese hamster ovary (CHO)cells adherent on a LID sensor surface before, and after addition ofsaponin.

FIG. 51 shows real time responses of CHO cells after pre-treatment withdifferent compounds and followed by saponin treatment.

FIG. 52 shows a time-dependent LID response of Chinese Hamster Ovary(CHO) cells before and after compound addition.

FIG. 53 shows the different kinetics of the mass redistribution due toagonist-induced GPCR activation.

FIG. 54 shows compound-dependant total responses of agonist-induced masschanges in the Stage 3 as highlighted in FIG. 16.

FIG. 55 shows a time-dependent LID response of Chinese Hamster Ovary(CHO) cells before and after compound addition. The compoundconcentration used is 10 μM for all compounds.

FIG. 56 shows a time-dependent LID response of engineered ChineseHamster Ovary (CHO) cells with over-expressed rat muscarnic receptorsubtype 1 (thus this cell line is termed as M1 CHO) before and aftercompound addition. The compound concentration used is 10 μM for allcompounds.

FIG. 57 compares the compound-dependant total responses in the Stage 3as highlighted in FIG. 16 for two distinct cell lines.

FIG. 58 shows a time-dependent LID response of two types of cells (CHOand M1 CHO) before and after addition of oxotremorine M (10 μM). Beforethe compound addition, the cells are pre-incubated either HBSS buffer(Invitrogen) (referred to “without DIP”) or with dynamin inhibitorypeptide (DIP) at a concentration of 50 μM for 45 minutes.

FIG. 59 shows a time-dependent LID response of two types of cells (CHOand M1 CHO) before and after addition of clonidine (10 μM). Before thecompound addition, the cells are pre-incubated either HBSS buffer(Invitrogen) (referred to “without DIP”) or with dynamin inhibitorypeptide (DIP) at a concentration of 50 μM for 45 minutes.

FIG. 60 shows a time-dependent LID response of two types of cells (CHOand M1 CHO) before and after addition of NECA (10 μM). Before thecompound addition, the cells are pre-incubated either HBSS buffer(Invitrogen) (referred to “without DIP”) or with dynamin inhibitorypeptide (DIP) at a concentration of 50 μM for 45 minutes.

FIG. 61 shows a GPCR agonist-induced directional mass redistributionwithin adlayer of quiescent A431 cells. Three GPCR agonists, bradykinin(100 nM), carbachol (10 μM) and clonidine (1 μM), induced time-dependentresponses of quiescent A431 cells, in comparison with that induced byEGF (8 nM). (F) Pretreatment of A431 with 10 μM AG1478 on the GPCRagonist- and EGF-induced responses.

FIG. 62 shows a schematic drawing shows the mechanism of EGF-inducedEGFR activation and one possible mechanism of G protein-coupled receptor(GPCR) agonist-induced EGFR transactivation. The GPCR agonist inducedEGFR transactivation could also be through other mechanisms: such asprotein kinase C pathway, or PI3K pathway. The bradykinin-induced DMRresponse of quiescent A431 cells, as showed in FIG. 61, could be throughprotein kinase C pathway.

FIG. 63 shows four classes of optical signatures induced by GPCRagonists. The optical signature is related to dynamic massredistribution within the bottom portion of quiescent A431 cells, asmonitored in real time with resonant waveguide grating biosensors. (a)G_(q)-type DMR signal, as exampled by thrombin (40 unit/ml). (b)G_(s)-type DMR signal, as exampled by epinephrine (25 nM). (c)G_(i)-type DMR signal, as exampled by α-MSH (α-melanocyte stimulatinghormone) (40 nM). (d) Net-zero DMR signal, as exampled by neurotensin(40 nM). The solid arrows (the same in the rest figures) indicated thetime when the agonist solution was introduced.

FIG. 64 shows the optical signatures of quiescent A431 cells induced byadenylate cyclase activators forskolin and NKH447.

FIG. 65 shows the pretreatment of quiescent A431 cells with forskolinand NKH447 completely abolished the DMR response mediated by 25 nMepinephreine. The pretreatment of cells with the HBSS only was used aspositive controls.

FIG. 66 shows the efficacies of agonists that trigger the G_(q)-typesignature. The dose-dependent kinetic responses and the correspondingsaturation curves were plotted for ATP (a, b), SLIGLR-amide (c, d),thrombin (e, f), and SLIGKV-amide (g, h), respectively. The finalconcentrations were indicated in the graphs.

FIG. 67 shows the efficacies of agonists that trigger the G_(s)-typesignature. The dose-dependent kinetic responses and the correspondingsaturation curves were plotted for epinephreine (a, b), adenosine aminecogener (ADCA) (c, d), and NECA (e, f), respectively.

FIG. 68 shows the dose-dependent kinetic responses and the saturationcurve of quiescent a431 cells induced by α-MSH (α-melanocyte stimulatinghormone).

FIG. 69 shows the switching of optical signatures induced by LPA(oleoyl-L-α-lysophosphatidic acid) from low doses (a) to high doses (b).

FIG. 70 shows the switching of optical signatures induced by HTMT fromlow doses (a) to high doses (b). The total amplitudes of the P-DMRsignals were plotted as a function of HTMT concentration (c), in orderto visualize the switching.

FIG. 71 shows the maximum percentage increases in intracellular Ca²⁺level, measured with the fluorescence intensity of Ca²⁺ obtained withFluo-3, were plotted as a function of PAR agonist.

FIG. 72 shows the effect of cytoskeletal modulators on the DMR signalsmediated by 100 nM trypsin (a) and 40 unit/ml thrombin (b). Themodulators used to pretreat the cells include latrunculin A,cytochalasin B, phalloidin, and nocodazole; each at 10 μM. The cellspretreated with the vehicle only (i.e., HBSS) were used as controls.

FIG. 73 shows the effect of kinase inhibitors on the DMR signalsmediated by 200 nM trypsin (a) and 40 unit/ml thrombin (b). The kinaseinhibitors were GF109203x (10 μM) and KN-62 (10 μM).

FIG. 74 shows the effect of YFFLNRP on the DMR responses mediated bythrombin (40 unit/ml), SFFLR-amide (20 μM) and SLIGKV-amide (20 μM), asplotted as the amplitudes of the P-DMR events as a function of YFFLNRPconcentration.

FIG. 75 shows cross desensitization of Ca²⁺ signaling mediated by PARs.After preceding treatment with trypsin, A431 cells were stimulated withthrombin (a), SFFLR-amide (b), SLIGKV-amide (c), and bradykinin (d). Onthe other hand, A431 cells were pre-stimulated with thrombin (e),SFFLR-amide (f), SLIGKV-amide (g), and bradykinin (h) before stimulatedwith trypsin. The final concentrations were 40 unit/ml, 200 nM, 20 μM,20 μM, and 100 nM for thrombin, trypsin, SFFLR-amide, SLIGKV-amide, andbradykinin, respectively. The time interval between two stimulations isabout 6 min. The solid arrows indicated the time when the solution wasadded (the same in other figures).

FIG. 76 shows cross desensitization of dynamic mass redistributionsignals mediated by PARs. After preceding treatment with trypsin, A431cells were stimulated with thrombin (a), SFFLR-amide (b), SLIGKV-amide(c), and bradykinin (d). On the other hand, A431 cells werepre-stimulated with thrombin (e), SFFLR-amide (f), SLIGKV-amide (g), andbradykinin (h) before being stimulated with trypsin. The finalconcentrations were 40 unit/ml, 200 nM, 20 μM, 20 μM, and 100 nM forthrombin, trypsin, SFFLR-amide, SLIGKV-amide, and bradykinin,respectively. The time interval between the two stimulations was about 1hour.

FIG. 77 shows the effect of cholesterol depletion by mβCD on theamplitudes of both P- and N-DMR signals mediated by 40 unit/ml thrombin(a) and 200 nM trypsin (b). In comparison, the effect of αCDα-cyclodextrin) was also included.

FIG. 78 shows the functional recovery of PAR signaling. After the cellsurface cholesterol was removal by mβCD and the cells were washed, athrombin solution was added separately into each well at specific time.The DMR signals were recorded in real time. Each graph is an average of7 independent responses.

FIG. 79 shows the effect of preceding EGF stimulation on PAR signaling(a) The trypsin-mediated Ca²⁺ mobilization. (b) The trypsin-mediated DMRsignal. (c) The thrombin-mediated DMR response. The final concentrationswere 100 nM EGF, 100 nM trypsin, and 40 unit/ml thrombin. The cellresponses with the pretreatment with HBSS buffer only were also includedas control.

FIG. 80 shows the multi-parameters of quiescent A431 cells in responseto 1 mM hydrogen peroxide as a function of time. (A) the shift in theincident angle; (B) the normalized PWHM; (C) the normalized peakintensity; (D) the normalized peak area. The arrows indicated the timewhen the solution was added.

FIG. 81 shows the dose dependent responses of quiescent A431 cellsadherent on a LID sensor surface before, and after addition of hydrogenperoxide.

FIG. 82 shows the effect of src inhibitors on the DMR signal ofquiescent A431 cells mediated by 1 mM H₂O₂.

FIG. 83 shows the effect of different redox states of quiescent cells onthe DMR responses mediated by 4 mM H₂O₂.

FIG. 84 shows the responses of quiescent A431 cells to EGF stimulation.(A) The dynamic shift in the incident angle as a function of time. (B)The normalized PWHM as a function of time. (C) Staining pattern of actinfilaments of untreated A431 with TR-phalloid. (D) Staining pattern ofactin filaments of A431 after treated with 16 nM EGF for 15 min andsubsequently stained with Texas Red-phalloid. The bar represents 40 μM.

FIG. 85 shows optical signatures of quiescent A431 cells mediatedthrough bradykinin B₂ receptor signaling by bradykinin: The PWHM (A) andthe intensity (B) of the resonant peak of the TM₀ mode. The arrowsindicated the time when a bradykinin solution was added.

FIG. 86 shows the wavelength shift between two time points during theassay as a function of compounds. The two time points were right beforethe compound addition (the baseline point), and 5 minutes after thecompound addition (the measured point). The difference between twoendpoints reflects the total amplitude of the P-DMR event mediated bybradykinin—a bradykinin B₂ receptor agonist. The B₂ receptor isendogenously expressed in A431 cells. The cells become quiescent beforethe bradykinin stimulation. In this example, a 384 well Coring Epicbiosensor plate was used. Each well contains A431 cells with aconfluency of ˜90%. Half of the wells were treated with bradykinin at100 nM, whereas other half of the wells were treated with the bufferHBSS only.

FIG. 87 shows the wavelength shift between two time points during theassay as a function of compounds. The two time points were right beforethe compound addition (the baseline point), and 5 minutes after thecompound addition (the measured point). The difference between twoendpoints reflects the total amplitude of the P-DMR event mediated bythrombin—a PAR1 receptor agonist. The PAR1 receptor is endogenouslyexpressed in CHO cells. The cells become partially quiescent byculturing the cells in the DMEM medium for 4 hours before the thrombinstimulation. In this example, a 384 well Coring Epic biosensor plate wasused. Each well contains CHO cells with a confluency of ˜90%. Half ofthe wells were treated with thrombin at 40 unit/ml, whereas other halfof the wells were treated with the buffer HBSS only.

FIG. 88 shows the wavelength shift between two time points during theassay as a function of thrombin concentration. The two time points wereright before the compound addition (the baseline point), and 5 minutesafter the compound addition (the measured point). The CHO cells weretreated with thrombin at different doses.

V. DETAILED DESCRIPTION

Before the present compounds, compositions, articles, devices, and/ormethods are disclosed and described, it is to be understood that theyare not limited to specific synthetic methods or specific biotechnologymethods unless otherwise specified, or to particular reagents unlessotherwise specified, as such may, of course, vary. It is also to beunderstood that the terminology used herein is for the purpose ofdescribing particular embodiments only and is not intended to belimiting.

I. DEFINITIONS

As used in the specification and the appended claims, the singular forms“a,” “an” and “the” include plural referents unless the context clearlydictates otherwise. Thus, for example, reference to “a marker orstimulatory event” includes mixtures of two or more such markers orstimulatory events, and the like.

Ranges can be expressed herein as from “about” one particular value,and/or to “about” another particular value. When such a range isexpressed, another embodiment includes from the one particular valueand/or to the other particular value. Similarly, when values areexpressed as approximations, by use of the antecedent “about,” it willbe understood that the particular value forms another embodiment. Itwill be further understood that the endpoints of each of the ranges aresignificant both in relation to the other endpoint, and independently ofthe other endpoint. It is also understood that there are a number ofvalues disclosed herein, and that each value is also herein disclosed as“about” that particular value in addition to the value itself. Forexample, if the value “10” is disclosed, then “about 10” is alsodisclosed. It is also understood that when a value is disclosed that“less than or equal to” the value, “greater than or equal to the value”and possible ranges between values are also disclosed, as appropriatelyunderstood by the skilled artisan. For example, if the value “10” isdisclosed the “less than or equal to 10” as well as “greater than orequal to 10” is also disclosed. It is also understood that thethroughout the application, data is provided in a number of differentformats, and that this data, represents endpoints and starting points,and ranges for any combination of the data points. For example, if aparticular data point “10” and a particular data point 15 are disclosed,it is understood that greater than, greater than or equal to, less than,less than or equal to, and equal to 10 and 15 are considered disclosedas well as between 10 and 15. It is also understood that any numberbetween the range and making the range is also disclosed, such asbetween 10 and 15, 10, 11, 12, 13, 14, and 15 are disclosed.

“Optional” or “optionally” means that the subsequently described eventor circumstance may or may not occur, and that the description includesinstances where said event or circumstance occurs and instances where itdoes not.

“Adhere” and “Adherent” or other forms of this word refer to two itemscoming into contact such that the two items have an affinity, such assticking, to one another. An adherent layer of cells on a substratewould be a layer of cells that, for example, would be adhered to thesurface, such that when gently washed with a buffer the cells would notbecome unadherent. It is understood that contact or other forms of thisword means two or more items being in proximity to one another such thatthey are considered to be touching. Contact does not typically require asticking. Contact can occur without having an adherence, for example.Attach or other forms of this word refer to a condition between two ormore items that is more permanent than adhere. It does not require, forexample, covalent attachment, but could. Thus, in order of the requiredstrength of the bond between two or more items, contact is less thanadhere which is less than attach. It is understood that these words havedistinct meanings, but that unless there is explicit indication to thecontrary or the skilled artisan would clearly understand it to be thecontrary, these words, can be interchanged within the description forwhich they are found in this specification. For example, if a sentenceincludes, “and the cells became adhered to the biosensor” it isunderstood that “and the cells became contacted to the biosensor” and“and the cells became attached to the biosensor” are also disclosed. Itis also understood that there can be a variety of adhered, contacted orattached items, such as cells or proteins.

“Amplitude” can refer to the amount or size of a particular response.For example, the output data from a biosensor can produce a resonantpeak that has a particular amplitude, such as intensity.

“Biological diffusion limited” refers to a process that is limited bythe diffusion of molecules in solution, and/or the penetration or uptakeof the molecules into the cells and subsequent diffusion inside thecells before reaching the target. For example, when a compound orstimulus-containing a solution is introduced to a medium which ispre-existed to cover the cells adherent on the surface of a biosensor,the compound or stimulus molecules have to diffuse in the resultedmixture (the medium and the solution) and take a certain time to reachthe cells. Afterwards, depending on the target with which that thecompound or stimulus will interact, the compound or stimulus moleculesmight have to take extra-time to reach the target determined by thepenetration or uptake of the molecules by the cell.

“Bulk index” refers to the absolute refractive index of a solution or amedium, determined by the compositions of the solution or the medium.“Bulk index change” refers to the resulted changes in refractive indexof a mixture solution when two solutions are mixed together, or asolution is added into and mixed with a medium or another solution.

“Guided mode” or “coupling mode” refers to a specific mode of lightcoupled into the waveguide substrate. There are two basic types ofguided waves (or modes) in a planar waveguide: TEm (transverse electricor s-polarized) and TMm (transverse magnetic or p-polarized), where m=0,1, 2, . . . is the mode number. Because the optical waveguide grating(OWG) biosensor is an evanescent-wave sensor and based on the resonantcoupling of light into a waveguide by means of a diffraction grating.There might be some different numbers of modes for each of the two basicmodes, for example, TM₀, TM₁, TM₂ . . . and TE₀, TE₁, TE₂, . . . . Thespecific mode that can be coupled into the waveguide substrate isdependent on the waveguide configuration and effective refractive indexof the given mode, which is determined by the refractive index of thecellular material and bulk solution that lies in the evanescent tail ofthat mode.

“Dose-dependent response” refers to a response, usually of a biosensoroutput or biosensor parameter, that changes with a change in dose(amount) of a stimulatory event such as addition of a compound.

“Incoupled light” refers to the light of certain bandwidth that is usedto illustrate the biosensor and thus coupled into the waveguide film.

“Label free biosensors” Many aspects of the disclosed compositions,methods and techniques involve the use of label free biosensors. As usedherein, label free biosensor refers to any sensor that can detect and/orgenerate a signal from an event or change (such as mass redistribution)in a cell without the need of labels such as fluorescent molecules.Label free biosensors generally comprise an optical transducer thatconverts an event in a cell into a quantifiable signal. Such signalgeneration can be accomplished in many ways. For example, direct surfacesensing methods include surface plasmon resonance (SPR) (Jordan & Corn,“Surface Plasmon Resonance Imaging Measurements of ElectrostaticBiopolymer Adsorption onto Chemically Modified Gold Surfaces”, Anal.Chem., 1997, 69:1449-1456), grating couplers (Morhard et al.,“Immobilization of Antibodies in Micropatterns for Cell Detection byOptical Diffraction,” Sensors and Actuators B, 2000, 70, 232-242),ellipsometry (Jin et al., “A Biosensor Concept Based on ImagingEllipsometry for Visualization of Biomolecular Interactions”, AnalyticalBiochemistry, 1995, 232, 69-72), evanascent wave devices (Huber et al.,“Direct Optical Immunosensing (Sensitivity and Selectivity),” Sensorsand Actuators B, 1992, 6, 122-126), and reflectometry (Brecht &Gauglitz, “Optical Probes and Transducers,” Biosensors andBioelectronics, 1995, 10, 923-936). The instrumentation typically usedto interrogate SPR or waveguide grating sensors utilizes an optical beamwith the appropriate spectral or angular content, such that when thisbeam is reflected by the sensing surface, the resonant angle orwavelength response becomes dominant in the output response.

Many label free biosensors are known examples of which are describedelsewhere herein. Examples of label free biosensors include non-contactbiosensors, label independent detection biosensors, label free opticalbiosensors, optical non-contact biosensors, optical-based biosensors,optical biosensors, optical label independent detection biosensors,waveguide grating-based biosensors, optical waveguide lightmodespectroscopy biosensors, evanescent wave devices. Various label freebiosensors and their use are described and referred to herein. Someparticular methods and modes of the use of label free biosensors aredescribed in the context of particular label free biosensors in order toprovide more specific examples of label free biosensors and their use.To avoid unnecessary duplication, such descriptions are not repeated forevery type of label free biosensor. However, it is to be understood thatwhen the use of particular biosensors in particular methods or modes isdescribed such use is illustrative of the use of any label freebiosensor in such methods and modes unless the context or nature of theuse would exclude one or more types of label free biosensor. Such use ofany and all biosensors in any and all methods and modes described herein(unless the context or nature of the use would exclude one or more typesof label free biosensor) is specifically contemplated and should beconsidered specifically disclosed. Thus, for example, if analysis ofEGF-induced EGFR signaling in a cell using a particular grating couplerbiosensor is described, then analysis of EGF-induced EGFR signaling in acell using any other appropriate label free biosensor is considereddisclosed. Thus, for example, analysis of EGF-induced EGFR signaling ina cell using a surface plasmon resonance-based biosensor would beconsidered disclosed.

“Time-dependent response” is a response, usually of a biosensor outputor biosensor parameter, that changes over time.

“Starvation medium” is any medium which decreases the proliferationcapacity of a culture of cells. When the starvation medium is used forincubating the cells or culturing the cells, the resulted cells becomequiescent.

Throughout this application, various publications are referenced. Thedisclosures of these publications in their entireties are herebyincorporated by reference into this application in order to more fullydescribe the state of the art to which this pertains. The referencesdisclosed are also individually and specifically incorporated byreference herein for the material contained in them that is discussed inthe sentence in which the reference is relied upon.

II. COMPOSITIONS AND METHODS

The disclosed compositions, methods, and techniques relate to the fieldof label free optical biosensors including waveguide grating-basedbiosensors for cell-based assay and techniques. The methods and systemsin general can relate to the direct optical—sensor field and,specifically, to systems and methods for using an optical labelindependent detection (LID) biosensor (e.g., waveguide grating-basedbiosensor) to monitor, for example, in real time, compound-induced massredistribution in living cells, including G protein coupled receptor(GPCR) agonisms and antagonisms, Epidermal Growth Factor Receptoractivity, cytoskeleton reorganization, cell death and cellproliferation, as well as cell signaling, desensitization, andtranslocation within living cells, as well as morphological changes ofadherent cells, cell deadhension, cell movements, and cells cultured ona biosensor. Direct optical sensor (DOS) technologies refers to thosethat utilize an optical transducer to convert the molecular recognitionor cellular event into a quantifiable signal without exciting thefluorescent or luminescent label(s). The technologies that rely on theexcitation and subsequent emission or luminescences of such labels arereferred to as indirect optical technologies, which can also be used incertain embodiments of the disclosed methods. Also disclosed are methodsfor screening the activity of compounds against cells, for exampleagainst receptors on cells, such as the GPCR or the EGFR or PDGFR orcytokine receptor.

Disclosed are compositions and methods that utilize label freebiosensors, such as waveguided grating-based biosensors, for monitoringand measuring directional mass redistribution (DMR) and which can couplethis DMR with a particular cell state or cellular event or cellactivity. It is understood that disclosed are “cell-biosensor” and“cell-biosensor-reagent” compositions which can be any of thecompositions disclosed herein in combination. For example, disclosed isa cell-biosensor-reagent composition comprised of A431 cells, abiosensor, and EGF.

For example, in certain disclosed assays, label free optical biosensorscan be used to assay the toxicity or proliferative effect of a compoundor compound or composition to a cell, and to measure the occurrence ofcell signal transduction events mediated, for example, through cellsurface receptors, such as receptor tyrosine kinases (RTKs), such asepidermal growth factor receptor (EGFR) or platelet derived growthfactor receptor (PDGF), or G protein-coupled receptors (GPCRs), orthrough internal signaling events, such as various signaling pathways orcytoskeleton rearrangement events. Label free optical biosensors asdisclosed herein can be used to assay the stimulation-mediatedtranslocation of a protein target or substrate recruitment, for example,to the nucleus, or to the membrane, or to the cytosol, or to otherorganelles (e.g., endosomes, endoplasmic reticulum (ER) or gogli ornuclei), or throughout various recycling pathways, or the uptake fromextracellular space (e.g., ligand binding, gene transfection or proteintransduction, phagocytosis, endocytosis, etc). In other examples, labelfree optical biosensors can be used to monitor the redistribution of aparticular target or a target complex among different functionalcompartments and/or among defined microenvironments in response tostimulation, or to measure the de novo synthesis of a particular target,or to examine the stimulation-mediated release from a particularcompartment(s) or location(s) (e.g., Ca mobilization due toagonist-induced Gq-coupled receptors or Ca ionophores). In this context,target is used as a molecule or cell component that is to be tracked oris part of an assay. In other examples label free optical biosensors canbe used to monitor the transport of a target molecule or a targetcomplex (e.g., bacteria, or viruses, or phages, or lipid particles, orexosome particles, etc.) from one cell to another cell (e.g., throughgap junction or ion channel), or either from or to the surroundingenvironment through, for example, a process known as excytosis or acontrol release process such as apoptosis or diffusion throughartificial holes at the cell surface membrane. These compositions andmethods in certain embodiments can be adapted to high throughput methodsby adoption and identification of a point during data collection wherebya determination can be made by collection of only one, two, or three,for example, separate points of data, which are predictive of the typeof cell event occurring during monitoring, which can be due to, forexample, a stimulatory event.

In certain embodiments, the disclosed compositions, methods, andtechniques relate to the use and the methods of use of waveguidegrating-based biosensors for monitoring adsorption, distribution and/ortoxicity of compounds acting on living cells adherent on biosensors.

In certain embodiments, the disclosed compositions, methods, andtechniques relate to methods of using of optical waveguide lightmodespectroscopy (OWLS) or resonant peak spectrum, or resonant band imagingof a given guided mode in combination with angular or wavelengthinterrogation to screen inhibitor or activator of cell proliferation.This method is applicable for high throughput screening.

In certain embodiments, the disclosed compositions, methods, andtechniques relate to methods of using optical waveguide lightmodespectroscopy (OWLS) or resonant peak spectroscopy of a given mode orresonant band imaging of a given mode that is applicable for highthroughput screening compound toxicity, as well as the other methodsdisclosed herein.

The disclosed compositions, methods, and techniques can useoptical-based biosensors to monitor the adsorption, distribution, and/ortoxicity of compounds acting on a living cell layer that is adherent onan optical biosensor. In another embodiment, the disclosed compositions,methods, and techniques provide methods for screening or monitoring theadsorption, distribution and/or toxicity of compounds acting on multipletypes of cells adherent on spatially addressable regions of an opticalsensor, or multiple biosensors located within a single well.

The disclosed compositions, methods, and techniques disclose a real timeand label free assays for compound adsorption, distribution and/ortoxicity screening and profiling. These methods can be used in multipledifferent assays (e.g., ADME/Tox, functional assays) and in fact, canintegrate multiple different assays into a single assay format.

In certain embodiments, the disclosed compositions, methods, andtechniques provide label-free measurements that are suitable for highthroughput screening of the effect of compounds on cell proliferation.In certain embodiments, the disclosed compositions, methods, andtechniques utilize optical waveguide lightmode spectroscopy (OWLS) orresonant peak spectroscopy of a given mode or resonant band imaging of agiven guided mode, rather than wavelength or angular shift alone, forhigh throughput screening inhibitors or activators of cellproliferation. This method uses the dependence of thepeak-width-at-half-maximum (PWHM) of incoupled peak of a given sensor oncell density. In certain embodiments of the disclosed compositions,methods, and techniques, the images of the incoupling resonance bands ofthe whole sensors in a microplate can be collected at the same time andused as a high throughput means to screen compounds for their effects oncell proliferation.

Disclosed are methods of screening modulators of cell signaling pathwaysusing optical biosensors. The methods can be applied to, for example,RTKs or GPCR, at the cell surface as well as to signaling eventsoccurring within the cell.

Disclosed are methods of screening modulators of cytoskeleton componentsusing optical biosensors. The methods are based on measuring release ofmacromolecules from a permeabilized cell induced by modulators ofcytoskeleton components. Specifically, the methods utilize specialchemicals or biologicals (e.g., saponin, streptolysin O, or the like) torender the plasma membrane of living cells sufficiently porous whichpermits soluble proteins inside the cells to diffuse away. Treatment ofcells with cytoskeleton-disrupting modulators lead to further releasebiological molecules including proteins and RNAs that are sequestered bycytoskeleton, resulting in the loss in mass which can be detected byoptical biosensors.

Provided is a discussion of optical biosensors, such as label freeoptical biosensors, such as optical waveguide light mode spectroscopyand waveguide grating-based biosensors and how they can be used indifferent configurations and combinations. This is followed by adiscussion of mass redistribution and how this can be related to opticalbiosensors. Also provided is a discussion of exemplary cell assays thatcan be performed using the optical biosensors disclosed herein as wellas additions and modifications to these assays, such as performing anassay first using an label free optical biosensor, but then having aparticular type of label coupled to one or more reagents in the assaywhich can be then used in a secondary or additional assay.

Disclosed are methods that can be used to perform a label freefunctional cell assay, such as a GPCR cell-based assay, which enablescompound screening and profiling. The disclosed methods allow one tostudy an endogenous GPCR in living cells without needing to geneticallyengineer the cell to over-express a receptor of interest, although, incertain embodiments, a cell having an over-expressed GPCR of interest ispreferably used in order to achieve high sensitivity and optimal assayresults.

The disclosed methods are capable of performing multiplexed cell-basedassays using a single sensor or using multiple sensors for comparison ofthe function of a compound among at least two different types of cellsoriginated from distinct parental cells or same parental cell (i.e., agiven specific type of cells). The methods can offer an advantage ofincreased throughput.

Disclosed are methods that can be used to perform multiplexed assaysusing a single sensor or using multiple sensors for confirming theinvolvement of a particular cellular target in the signaling or cellularevents measured in response to stimulation. The methods can use a singlesensor with at least two distinct regions: one without modification andanother with modification; or can use at lease two sensors within a samechamber or separated chambers: one without modification and another withmodification. The modified areas of sensors, for example, can haveprinted or deposited spots containing reagents/genes or interference RNA(RNAi) or antisense oligonucleotides or antisense/antigene peptidenucleic acid (PNA) or proteins or antibody such that when cells arecultured onto and overlaid with these regions, the adherent cells uptakethese reagents/materials and become transfected. Such methods arereferred to as positional surface-mediated transfection. Oncetransfected with these materials, a particular target in the cellbecomes either over-expressed through the surface-mediated genetransfection or protein delivery, or can be down-regulated throughantisense/antigene suppression or RNA interference or knockout orantibody blockage. US2004/0023391A1 and U.S. Pat. No. 6,544,790, whichare herein incorporated in their entireties, but at least for materialrelated to methods for delivery to cells. The positionalsurface-mediated transfection allows the detection ofstimulation-induced responses of a particular type of cells with andwithout the specific target. The positional surface mediatedtransfection can be considered a stimulatory event. Therefore, thepresent methods can be used to confirm the involvement of the specificcellular target in the signal or cellular events measured using thelabel free optical biosensors. The deposition or printing of thematerials onto the sensor surface can be achieved using state-of-the-artmethods, including, but not limited to, contact printing such as pinprinting technology (U.S. Pat. No. 5,807,522 A or U.S. Pat. No.6,101,946 A) or microstamping methods (U.S. Pat. No. 5,731,152),capillary dispensing devices (U.S. Pat. No. 5,807,522) andmicropipetting devices (U.S. Pat. No. 5,601,980) or non-contact printingsuch as piezo-driven printing or micro/nanodispenser devices (U.S. Pat.No. 6,656,432 B1, EP0895082 B1 or U.S. Pat. No. 6,399,396 B1).

Disclosed are methods to perform label-free biosensor-based cell assaysthat utilize multiple penetration depths. Also, disclosed are devicesthat allow one to perform such assays in simplexed or multiplexed assayformats.

According to the OWLS, the PWHM changes of the TM modes are moresensitive to surface inhomogeneities than that of the TE mode. The PWHMincreases when the cells start to spread on the surface, reaches itsmaximum at about 50% cell coverage, and decay back to the original levelafterwards.

Disclosed herein it has been shown that the adsorption, distribution andtoxicity of a compound to a highly confluent cell layer near thecell-sensor interface can be monitored in real time, as documented bycompound toxicity-induced wavelength or angular shifts using opticalbiosensors.

Disclosed are methods to study the cellular functions of reactive oxygenspecies (ROS) probed with optical biosensors. Also, disclosed aremethods to evaluate the redox states of cultured cells, as well as toscreen modulators that affect the redox states of cultured cells as wellas the ROS signaling. Reactive oxygen species are molecules likehydrogen peroxide, ions like the hypochlorite ion, radicals like thehydroxyl radical, and the superoxide anion which is both ion andradical. Substances that have the ability to oxidize other substancesare said to be oxidative and are known as oxidizing agents, oxidants oroxidizers. Oxidants are usually chemical substances with elements inhigh oxidation numbers (e.g., H₂O₂, MnO₄ ⁻, CrO₃, Cr₂O₇ ²⁻, OsO₄) orhighly electronegative substances that can gain one or two extraelectrons by oxidizing a substance (O₂, O₃, F₂, Cl₂, Br₂). Reactiveoxygen species are formed by several different mechanisms: (1) theinteraction of ionizing radiation with biological molecules; (2) as anunavoidable byproduct of cellular respiration (e.g., some electronspassing “down” the respiratory chain leak away from the main path(especially as they pass through ubiquinone) and go directly to reduceoxygen molecules to the superoxide anion); (3) synthesized by dedicatedenzymes in phagocytic cells like neutrophils and macrophages (e.g.,NADPH oxidase (in both type of phagocytes); or myeloperoxidase (inneutrophils only)). ROS are essential, but it is important that theattempt to limit the production of ROS not succeed too well. Because ROShave important functions to perform in the cell. Examples are (1) Thecells of the thyroid gland must make hydrogen peroxide in order toattach iodine atoms to thyroglobulin in the synthesis of thyroxine. (2)Macrophages and neutrophils must generate ROS in order to kill sometypes of bacteria that they engulf by phagocytosis. (3) Neutrophils (butnot macrophages) also kill off engulfed pathogens by using the enzymemyeloperoxidase which catalyzes the reaction of hydrogen peroxide (madefrom superoxide anions) with chloride ions to produce the stronglyantiseptic hypochlorite ion. (4) Much biological energy is stored andreleased by means of redox reactions. Photosynthesis involves thereduction of carbon dioxide into sugars and the oxidation of water intomolecular oxygen. The reverse reaction, respiration, oxidizes sugars toproduce carbon dioxide and water. As intermediate steps, the reducedcarbon compounds are used to reduce nicotinamide adenine dinucleotide(NAD⁺), which then contributes to the creation of a proton gradient,which drives the synthesis of adenosine triphosphate (ATP) and ismaintained by the reduction of oxygen. In animal cells, mitochondriaperform similar functions. The term redox state is often used todescribe the balance of NAD⁺/NADH and NADP⁺/NADPH in a biological systemsuch as a cell or organ. The redox state is reflected in the balance ofseveral sets of metabolites (e.g., lactate and pyruvate,beta-hydroxybutyrate and acetoacetate) whose interconversion isdependent on these ratios. An abnormal redox state can develop in avariety of deleterious situations, such as hypoxia, shock, and sepsis.It is understood that the flux and effect of all of the molecules,compounds, and compositions discussed in this paragraph can beidentified, or otherwise used in the methods disclosed herein.

Disclosed are methods to examine the cross communication among familymembers of targets such as GPCRs, RTKs, and others, as well as amongdistinct classes of targets such as between a GPCR and a RTK. Cells needto communicate with one another, whether they are located close to eachother or far apart. Extracellular signaling molecules regulateinteractions between cells. The basic mechanism requires a ligand(signaling molecule) to interact with its receptor so as to convert theextracellular signal to an intracellular signal. This process is calledsignal transduction and can occur in several forms. First, if a signalis needed to communicate with the entire organism; the signalingmolecule is secreted into the bloodstream. For example, endocrinesignaling requires a cell to synthesize and secrete a hormone into thecirculatory system. That hormone is then recognized by a specific targetcell protein (receptor) either on the plasma membrane or within thecytoplasm. Second, in other situations the signal is required to actlocally. For example, paracrine signaling molecules (local mediators)can be released by a neighboring cell, diffuse locally through the ECM,and stimulate a close target cell. For example, growth anddifferentiation factors are thought to act primarily as paracrinesignaling molecules. A third form of communication is neuronalsignaling. This type of signal transduction can occur over longdistances, however the delivery is by way of long cellular processescalled axons. Neuronal signals can act on target cells or on otherneuronal cells. The signal travels through the axon as an electricalimpulse that upon reaching the axon terminus it is converted into achemical signal called a neurotransmitter. The fourth style of signaltransduction is the most short-range of all. It typically does notrequire the release of a secreted molecule. For example,contact-dependent signaling requires the transduction to be completedwhen the signaling molecule anchored in the plasma membrane of thesignaling cell to bind to the receptor molecule embedded in the plasmamembrane of the target cell. Contact-dependent signaling can also occurin the form of a cell interacting with the extracellular matrices. Eachcell is able to respond to a limited set of signals due to itsspecialized function as well as its limited types of receptors.Additionally, each cell responds to a signal molecule differently. Inthis case, for example, the neurotransmitter, acetylcholine canstimulate one type of muscle cell to contract (skeletal) or inhibitcontraction in another (cardiac). Acetylcholine can also stimulatecertain cells to secrete the contents of their secretory vesicles.Alternatively, similar receptors can activate different intracellularsignaling pathways, or the ligand binds to different receptors. In alinear model, signaling pathways can be viewed that the main flow ofinformation is sequential and goes through a linear chain ofintermediate steps from the receptor to a particular cell function.However, because of the complexity of cell biology, instead of thelinear information flow, the signaling mediated by a stimulationconsists of a number of modules that are connected by feedback involvinga diffusion step (diffusible feedback systems) or that are physicallylinked to complexes of signaling proteins and/or scaffolding proteins.For example, a diffusible feedback module can be seen in the positiveand negative feedback loops by which calcium and theinositol-trisphosphate receptor regulate cytosolic calciumconcentration. These positive and negative feedback loops play importantroles in signaling cross-communications. For example, signaling of manymitogenic GPCRs has been demonstrated to cross-communicate with EGFRsignaling in either a negative or positive way. The activation of theseGPCRs also leads to the activation of EGFR in the same cells, eitherthrough protein kinase C or β-arrestin which acts an adaptor protein.

Disclosed are methods to screen modulators against a specific target ora class of targets in a high throughput format, based on at least twoendpoint measurements.

a) Use of OWLS for Monitoring Cell Health

The present compositions, methods, and techniques disclose the use ofoptical waveguide lightmode spectroscopy or resonant peak spectrum of agiven guided mode or resonant band imaging for high throughput screeningcompound toxicity. Disclosed are measurements that are suitable for highthroughput screening compound toxicity using optical-based biosensors.The disclosed methods, compositions, and techniques, can be used tomonitor the health of a cell or cell population. The term “health”refers to the overall state of the cell in terms of viability and cellfunction. There are many ways in which a cell can display negativeeffects on its health, such as a decrease in cell division, a decreasein cell function, such as protein or mRNA production, a decrease in cellsignaling, and/or an increase in proteins related to cell death, forexample. Traditionally, cell health evaluation used fluorescencestaining methods or other means to examine cell membrane integrity, orthe function of a particular target protein (e.g., mitochondrialdehydrogenases), or the synthesis of a particular gene product, or theincorporation of a labeled nucleotide into the DNA or RNA, or theintegrity of chromosome in the nuclei of the cell. In certainembodiments, the methods utilize the dependence of thepeak-width-at-half-maximum (PWHM) of incoupled peaks of a given sensoron cell density, cell death patterns and cell layer inhomogeneities thatare modified due to the toxicity of a compound. Compound toxicityresults in the formation of three populations of cells, viable, affectedand dead cells, on the waveguide film surface. The resulted increasedinhomogeneities of the surface lead to resonance peak broadening, andeven splitting. The resonance peak broadening and splitting can be usedas a signature for compound toxicity. Either the resonance peak spectraor the whole sensor resonance images can be collected and analyzed atcertain time after cells are exposed to a compound.

The disclosed compositions, methods, and techniques provide methods tomonitor the adsorption, distribution and toxicity of a compound actingon a cell layer cultured on an optical sensor. The methods can involvethe real-time measurements of the angular or wavelength shifts for alayer of cells in response to a compound administered to or incubatedwith the cell, due to the mass redistribution in the cell layer, usingoptical biosensors. These methods are useful for studying the kineticsand mechanisms of cell toxicity and apoptosis. Also disclosed are highthrough-put methods.

2. High Through Put Methods for Monitoring Cell Health

In certain embodiments, these methods utilize an optical interrogationsystem that can simultaneously monitor multiple waveguide gratingbiosensors, and/or obtain resonant peak spectra of a given guided modeof multiple biosensors, and/or visualize resonant band images of a givenguided mode of multiple biosensors. For example, an optical angularinterrogation system, as disclosed in U.S. patent application Ser. No.10/602,304, filed Jun. 24, 2003, having publication no. US-2004-0263841,published Dec. 30, 2004 and U.S. patent application Ser. No. 11/019,439,filed Dec. 21, 2004, and U.S. patent application for “OPTICALINTERROGATION SYSTEM AND METHOD FOR 2-D SENSOR ARRAYS” by N. Fontaine etal., filed on Apr. 5, 2005, all of which are herein incorporated intheir entireties by reference but at least for biosensors and theiruses.

U.S. patent application Ser. No. 10/602,304, having publication no.US-2004-0263841 and U.S. patent application Ser. No. 11/019,439, filedDec. 21, 2004, and U.S. patent App. for “OPTICAL INTERROGATION SYSTEMAND METHOD FOR 2-D SENSOR ARRAYS” by N. Fontaine et al., filed on Apr.5, 2005 provide a launch system for generating an array of light beamssuch that each illuminates an RWG sensor with a dimension of ˜200μm×3000 μm and a receive system for receiving all responses, asindicated by the angles of the light beams reflected from these sensors.This system allows, for example, up to 7×7 well sensors to besimultaneously sampled at a rate of 3 seconds (an example was shown inFIG. 1). This means that cell health evaluation for 96 samples in a 96well microplate can be done within several seconds. Another exemplarysystem, as disclosed in U.S. application Ser. No. 10/993,565, filed Nov.18, 2004 by N. Fontaine et al. and “METHOD FOR ELIMINATING CROSSTALKBETWEEN WAVEGUIDE GRATING-BASED BIOSENSORS LOCATED IN A MICROPLATE ANDTHE RESULTING MICROPLATE” by Y. Fang et al., filed on Apr. 5, 2005 (Bothof which are incorporated in their entireties and at least for materialrelated to biosensors, scanning devices, and microplates) uses anarrayed optical fibers for generating an arrayed light such that eachilluminates one biosensor and receives the responses from the samebiosensors; and uses the controlled scanning module to collect responsesfrom multiple areas within a single sensor as well as from multiplebiosensors within a microplate in a sequential manner. Such systemallows the cell health evaluation to be done within about 30 seconds.

3. Optical Based Biosensors

Optical-based biosensors have been used to detect a variety ofbiomolecular interactions including oligonucleotides, antibody-antigeninteractions, hormone-receptor interactions, and enzyme-substrateinteractions. There have been relatively few of reports describing theuse of optical label free techniques for cell-based studies. Forexample, optical waveguide grating-based biosensor has been used toinvestigate the adhesion and spreading of animal cells (J. J. Ramsden,et al., “Kinetics of Adhesion and Spreading of Animal Cells,”Biotechnol. Bioeng. 1994, 43, 939-945); and surface plasmon resonance(SPR) has been used for studying ligand-induced intracellular reactionsof living cells (M. Hide, et al, “Real-time Analysis of Ligand-InducedCell Surface and Intracellular Reactions of Living Mast Cells Using aSurface Plasmon Resonance-Based Biosensor,” Anal. Biochem. 2002, 302,28-37).

Optical-based biosensors generally consist of two components: a highlyspecific recognition element and an optical transducer that converts themolecular recognition event into a quantifiable signal. Direct surfacesensing methods include surface plasmon resonance (SPR) (Jordan & Corn,“Surface Plasmon Resonance Imaging Measurements of ElectrostaticBiopolymer Adsorption onto Chemically Modified Gold Surfaces,” Anal.Chem., 1997, 69:1449-1456), grating couplers (Morhard et al.,“Immobilization of Antibodies in Micropatterns for Cell Detection byOptical Diffraction,” Sensors and Actuators B, 2000, 70, 232-242),ellipsometry (Jin et al., “A Biosensor Concept Based on ImagingEllipsometry for Visualization of Biomolecular Interactions,” AnalyticalBiochemistry, 1995, 232, 69-72), evanascent wave devices (Huber et al.,“Direct Optical Immunosensing (Sensitivity and Selectivity),” Sensorsand Actuators B, 1992, 6, 122-126), and reflectometry (Brecht &Gauglitz, “Optical Probes and Transducers,” Biosensors andBioelectronics, 1995, 10, 923-936). The instrumentation typically usedto interrogate SPR or waveguide grating sensors utilizes an optical beamwith the appropriate spectral or angular content, such that when thisbeam is reflected by the sensing surface, the resonant angle orwavelength response becomes dominant in the output response. A commonfeature is that both SPR and grating coupler (i.e., OWG or RWG)technologies are sensitive to refractive index changes at/near thesensor surface.

One major application of this technology as a biosensor is to monitor insitu the interfacial behaviors of specific analytes under the conditionsof different surface properties and different solution characteristics.This technology allows label free detection, unlike most of the currenttechnologies which requires specific labels for readout the interactionsignals. The disadvantages associated with the labeling is that labelingis not only labor-intensive and costly, but also has potential tointerference with the biological properties of target biologicals orcompounds such that the data interpretation would be difficult and falseinformation might be generated from assays. However, as disclosedherein, these disadvantages can be reduced when non-labelingvisualization techniques are used or when labeling is used inconjunction with the non-labeling techniques disclosed herein. It isalso understood that any of the sensors disclosed herein can be used ina variety of ways, including in a multiplex manner, for example, suchthat the multiplexing is done in using multiwell plates, such as amodified 96 well microplate. As disclosed herein, the label freebiosensors, such as a RWG or OWG biosensor can be used in conjunctionwith cells and activities of the cells can be monitored. The cells canbe cultured on the biosensors such that the cultured cells are adherentto the biosensor, much like when cells are cultured on a conventionalplate and become adherent to the bottom surface of the plate. When thecells are cultured on the disclosed biosensors there is a change in theoutput of the biosensor. FIG. 1 shows an example of the output ofcultured cells on the system. FIG. 2 shows a diagram of an opticalwaveguide grating sensor. In this figure the cells are cultured on topof the sensor. When a light source, such as a laser, is directed at thesensor at varying angles, at a specific set of angles the light will becoupled into the sensor. At other angles the light will either bedirectly reflected or pass through the sensor. As disclosed herein, uponcell manipulation such as stimulation of a receptor at the surface ofthe cell, there is a mass redistribution that takes place within thecell. This mass redistribution causes a number of things, one of whichis a change in the angle at which the light will couple into the sensor.This change in angle can be utilized to identify events taking placewithin the cell, and it is understood as described herein thatparticular events can have a signature profile with respect to theoutput associated with the biosensor based on the mass redistributionthat takes place within the cell.

Unlike conventional cell proliferation assays that generally requirelabels and lengthy incubation steps, certain embodiments of thedisclosed compositions, methods, and techniques provide methods based onoptical waveguide lightmode spectroscopy (OWLS) or resonant peakspectroscopy of a given guided mode or resonant band imaging of a givenguided mode that do not require any labels. Furthermore, in certainembodiments the disclosed compositions, methods, and techniqueseliminate any extra treatment steps including reagent reaction andwashing steps. In addition, in certain embodiments, the disclosedcompositions, methods, and techniques, such as the cell proliferationassays can be carried out under standard culture conditions in theabsence and presence of compounds of interest only, without theinterference of any other reagents which are generally required foralmost all conventional methods. The presence of other reagents couldresult in the misinterpretation of assays results: (J. J. Ramsden, etal., “Kinetics of Adhension and Spreading of Animal Cells”, Biotechnol.Bioeng. 1994, 43, 939-945) as these reagents themselves could have adirect effect on cell proliferation; (M. Hide, et al., “Real-timeAnalysis of Ligand-Induced Cell Surface and Intracellular Reactions ofLiving Mast Cells Using a Surface Plasmon Resonance-Based Biosensor,”Anal. Biochem. 2002, 302, 28-37) compounds to be screened could have aneffect on these reagents, rather than cell proliferation. For example,compounds that inhibit cellular mitochondrial dehydrogenases directlycould result in the suppression of the conversion of MTT, therebyleading to false positives when a MTT assay is used to screen modulatorsagainst another particular target of interest.

In certain embodiments, the disclosed compositions, methods, andtechniques provide ultra high throughput screening approaches to “fishout” inhibitors and activators, unlike other current label free cellproliferation assays including optical waveguide sensing approach whichinvolves the real-time measurements of the angular or wavelength shiftsdue to cell proliferation. Because cell proliferation is generally aslow process (e.g., it takes many hours, days or even weeks) andgenerally requires 37° C. incubation, label free proliferation assaysother than those disclosed herein which generally collects signals atroom temperature are difficult to be implemented for high throughputscreening.

The methods disclosed herein can provide accurate measurements withoutany extra reagents, and are easy to use and integrate with otherfunctional screening. For example, there can be no need to store ormanipulate radioactive or other substances (e.g., light-sensitivefluorescent compounds).

While others have used optical waveguide-based biosensors for cellproliferation assays, their use of optical waveguide-based biosensorsmonitored the wavelength shift of the sensors due to attachment of cellsin the presence of different concentrations of a compound for a givennumber of starting cells (Cunningham, B. T., et al., “Label-Free Assayson the BIND System,” J. Biomol. Screening 2004, 9, 481-490 and U.S.Patent Application Publication No. US20030068657 A1 for “Label-freemethods for performing assays using a colorimetric resonant reflectanceoptical biosensor” SRU Biosystems LLC by Lin, Bo et al.). These methodscan be used, in certain situations, for examining IC₅₀s of a compound oncell proliferation. However, these methods are not suitable for highthroughput screening, as the methods disclosed herein are. Disclosedherein, waveguide-based biosensors can be used to not only monitor theagonist-induced directional mass redistribution due to the activation ofG protein coupled receptor (GPCR) or receptor tyrosine kinase such asEGFR in living cells, but also to study signaling pathways or cellularmechanism that lead to directional mass redistribution.

a) OWLS and Cell Toxicity

According to the OWLS, patterns and inhomogeneities on the surface ofthe waveguide can produce broadening and fine structure in the incoupledpeak spectra. Instead of one sharp resonance peak of each mode forhomogeneous surface immobilization on the sensor, these fine structuresfor sensors with inhomogeneous attachment of biologicals or materialsobserved experimentally and theoretically include, but not limited to,at least one shoulder (i.e., secondary) peak appearing with the mainresonance peak of each mode, and well-separate double (or more) peak foreach mode (see Horvath, R., et al. “Effect of patterns andinhomogeneities on the surface of waveguides used for optical waveguidelightmode spectroscopy applications”, Appl. Phys. B. 2001, 72, 441-447;Voros, J., Graf, R. et al., “Feasibility Study of an OnlineToxicological Sensor Based on the Optical Waveguide Technique,”Biosensors & Bioelectronics 2000, 15, 423-429 the references therein areincorporated). Previously, researchers have observed that during cellattachment and spreading on the waveguide, the incoupled peaks arebroadened, while regular microstructures on the grating produce shiftsand splitting of the peaks. The broadening of the resonance peaks hasbeen used as fingerprint of cell attachment and spreading.

4. Optical Biosensors and Mass Redistribution in Cells

The instrumentation typically used to interrogate SPR or waveguidegrating sensors utilizes an optical beam with an appropriate spectral orangular content, such that when this beam is reflected by the sensingsurface, the resonant angle or wavelength response becomes dominant inthe output beam. Specifically, a planar optical waveguide used as asensor consists of a substrate, a waveguiding film and a cover medium,where the cover medium is the substance to be characterized bydetermining the refractive index. The planar waveguide-based biosensorscan be used to detect changes in the media surrounding the waveguide asthe electromagnetic field propagating in the waveguide will extend intothe surrounding media as an evanescent electromagnetic field (the depthis referred to the penetration depth or sensing volume). When massredistribution occurs within the sensing volume, a response change isobserved as an angular or spectral change in the reflected beam. Theangular shift can be measured to obtain the kinetics of the massredistribution response signal. In addition, because of that, distinctcellular responses would contribute differently to the overall massredistribution signals. For example, cell detachment from theextracellular matrices occurs at/near the sensor surface, and thereforecould lead to significantly greater responses than those occurringinside the cells.

Biological cells are complex structures with components ranging in sizefrom nanometers to tens of microns, as illustrated in FIG. 9. The cellconsists of a cytoplasm (typically 5-30 μM) containing numerousorganelles. The largest organelle is the nucleus, whose size rangestypically between 3 and 10 μm. The nucleus is filled with DNA-proteincomplexes and proteins, the most important one being chromatin.Mitochondria are small organelles comprised of a series of foldedmembranes with sizes typically ranging from 0.5-1.5 μm. Other cellcomponents include endoplasmic reticulum (ER) (typically 0.2-1 μm),lysomes (typically 0.2-0.5 μm), peroxisomes (typically 0.2-0.5 μm),endosomes (typically ˜100 nm), and golgi.

a) Optical Waveguide Grating-Based Surface Sensing Technology

Resonant waveguide grating sensors (RWG) and optical waveguide grating(OWG) can be used interchangeably. The RWG biosensor is anevanescent-wave sensor, based on the resonant coupling of light into awaveguide by means of a diffraction grating. The RWG-based surfacesensing technology takes advantage of the evanescent field, whichpenetrates less than a wavelength out of the waveguide surface, toselectively respond to the adsorption of immobilized chemical andbiological molecules over a given spectral bandwidth.

An example of an optical LID biosensor, such as 1004 FIG. 10, is a SPRsensor 1004 or a waveguide grating based sensor 1004. Otheroptical-based biosensors can also be used such as ellipsometry devices,evanescent wave devices, and reflectometry devices. For a more detaileddiscussion about the structure and operation of these two types ofoptical LID biosensors, such as 1004, are provided in U.S. Pat. No.4,815,843 entitled “Optical Sensor for Selective Detection of Substancesand/or for the Detection of Refractive Index Changes in Gaseous, Liquid,Solid and Porous Samples” and K. Tiefenthaler et al. “Integrated OpticalSwitches and Gas Sensors” Opt. Lett. 10, No. 4, April 1984, pp. 137-139,which are both herein incorporated in their entireties at least formaterial related to biosensors. In particular, optical biosensorsdisclosed in U.S. Patent App. 60/701,445, filed Jul. 20, 2005, for“Label-Free High Throughput Biomolecular Screen System and Method” andU.S. patent application Ser. No. 11/019,439, filed Dec. 21, 2004, andU.S. patent App. for “OPTICAL INTERROGATION SYSTEM AND METHOD FOR 2-DSENSOR ARRAYS” by N. Fontaine et al., filed on Apr. 5, 2005, all ofwhich are herein incorporated in their entireties by reference but atleast for biosensors and their uses.

(1) Symmetry Waveguide Grating Biosensors

An example of a symmetry waveguide grating biosensor is a gratingcoupler or coupled biosensors. Examples of grating coupled biosensorscan be found in Jordan & Corn, “Surface Plasmon Resonance ImagingMeasurements of Electrostatic Biopolymer Adsorption onto ChemicallyModified Gold Surfaces,” Anal. Chem., 1997, 69:1449-1456; Morhard etal., “Immobilization of antibodies in micropatterns for cell detectionby optical diffraction,” Sensors and Actuators B, 2000, 70, 232-242; andTiefenthaler, K., and W. Lukosz, “Sensitivity of grating couplers asintegrated optical chemical sensors” J. Opt. Soc. Am. B, 1989, 6,209-220 and are herein incorporated by reference in their entireties butat least for material related to grating coupled biosensors.

Grating coupler biosensors are evanescent-wave sensors based on theresonant coupling of light into a waveguide by means of a diffractiongrating. The grating coupler sensor consists of the combination of awaveguide and diffraction grating. FIG. 2 a shows a classical four layerwaveguide biosensor consisting of a thin film of a high refractive index(e.g., n_(F)˜2.36 for Nb₂O₅) material with a thickness of d_(F) on asubstrate of lower index (e.g., n_(s)˜1.50 for 1737 glass). Immobilizedon the waveguide film is an adlayer of biologicals with a refractiveindex (n_(A)) around 1.4 and a thickness d_(A), and on top of the entiresensor structure is the cover medium, being the biological solution withindex (n_(c)) around 1.35. In this conventional configuration, therefractive index of the waveguide thin film is at least 1% higher thanthat of the substrate of lower index, for example, by 1%, 5%, 10%, 20%,30%, 50%, 70%, or 100%. The refractive index of the substrate of lowerindex is higher than that of the cover medium, for example, by 5%, 7%,10%, 15%, 20%, 30%, or 50%. The refractive index of the cover medium,generally aqueous medium for cell-based assay applications, is typicallyaround 1.32, 1.35, and 1.38.

The guided waves or modes in planar waveguide are TE_(m) (transverseelectric or s-polarized) and TM_(m) (transverse magnetic orp-polarized), where n=0, 1, 2, . . . is the mode number. A given guidedmode refers to, for example, TM₀, TE₀, TM₁, TE₁, etc. A laserilluminates the waveguide at varying angles and light is coupled intothe waveguide only at specific angles determined by the effectiverefractive index of the guided mode, denoted as N. Since the evanescenttails of the light mode propagates in the substrate and cover media butstill along the film, the light modes experience or sense all threemedia at the same time. It means that the refractive index experiencedby the traveling light modes is a weighed mixture of the threerefractive indices. The effective refractive index N can be calculatednumerically from the mode equation, which can be written in thefollowing form for a four layer waveguide assuming that the thickness ofthe thin adlayer is less than the wavelength of the light (d_(A)<<λ)[Tiefenthaler, K., and W. Lukosz, “Sensitivity of grating couplers asintegrated optical chemical sensors” J. Opt. Soc. Am. B, 1989, 6,209-220]:

$\begin{matrix}{0 \cong {{\pi \; m} - {{k\left( {n_{F}^{2} - N^{2}} \right)}^{0.5}\left( {d_{F} + {d_{A}{\frac{n_{A}^{2} - n_{C}^{2}}{n_{F}^{2} - n_{C}^{2}}\left\lbrack \frac{\left( {N/n_{C}} \right)^{2} + \left( {N/n_{A}} \right)^{2} - 1}{\left( {N/n_{C}} \right)^{2} + \left( {N/n_{F}} \right)^{2} - 1} \right\rbrack}^{\sigma}}} \right)} + {\arctan \left\lbrack {\left( \frac{n_{F}}{n_{S}} \right)^{2}\left( \frac{N^{2} - n_{S}^{2}}{n_{F}^{2} - N^{2}} \right)^{0.5}} \right\rbrack} + {\arctan \left\lbrack {\left( \frac{n_{F}}{n_{C}} \right)^{2}\left( \frac{N^{2} - n_{C}^{2}}{n_{F}^{2} - N^{2}} \right)^{0.5}} \right\rbrack}}} & (1)\end{matrix}$

Here, k=2π/λ, where λ is the vacuum wavelength of the guided light. σ isa mode type number which equals 1 for TE and 0 for TM modes.

If light is coupled into the waveguide by a surface-relief grating, Ncan be calculated from the incoupling angle:

(±)N=N _(air) sin(θ)+lλ/Λ  (2)

Where N_(air)=1.0003 is the refractive index of air, θ the angle ofincidence measured in air, λ the wavelength, Λ the grating period andl=±1, ±2, . . . the diffraction order. The plus and minus signs on theleft side of this equation hold for guided modes propagating in the +xand −x directions, respectively.

The induced effective refractive index change ΔN in the waveguide in thegrating area lead to changes Δθ as described in following equation:

ΔN=n _(air) cos(θ)Δθ  (3)

Since the laser light is coupled to and propagates parallel to thesurface in the plane of a waveguide film, this creates anelectromagnetic field (i.e., an evanescent wave) in the liquid adjacentto the interface. The amplitude (Em) of the evanescent wave decaysexponentially with increasing distance d from the interface:

$\begin{matrix}{{{E_{m}(d)} = {{E_{m}(0)}{\exp \left( \frac{- d}{\Delta \; Z_{C}} \right)}}}{with}} & (4) \\{{\Delta \; Z_{C}} = {\frac{1 - \sigma}{{k\left( {N^{2} - n_{C}^{2}} \right)}^{0.5}} + \frac{{\sigma \left\lbrack {\left( {N/n_{F}} \right)^{2} + \left( {N/n_{C}} \right)^{2} - 1} \right\rbrack}^{- 1}}{{k\left( {N^{2} - n_{C}^{2}} \right)}^{0.5}}}} & (5)\end{matrix}$

is the penetration depth of the waveguide mode with high intensity intocover medium.

A given mode type propagates only as a guide wave if two conditions needto be fulfilled: (a) the refractive index of the waveguide film has tobe at least 1% larger than the surrounding substrate and cover mediumrefractive indices; and (2) the thickness of the waveguide film islarger than a well-defined value, call the cut-off thickness d_(C):

$\begin{matrix}{d_{C} = {\frac{1}{{k\left( {N_{F}^{2} - n_{m\; {ax}}^{2}} \right)}^{0.5}}\left( {{\pi \; m} + {\arctan \left( {\left( \frac{n_{F}}{n_{m\; i\; n}} \right)^{2\sigma}\left( \frac{n_{m\; {ax}}^{2} - n_{m\; i\; n}^{2}}{n_{F}^{2} - n_{m\; {ax}}^{2}} \right)^{0.5}} \right)}} \right)}} & (6)\end{matrix}$

Where n_(min)=min{n_(s),n_(C)} and n_(max)=max{n_(s),n_(C)}. It is knownthat when the film thickness approaches the cut-off thickness, theeffective refractive index, N, of the mode approaches n_(max).Furthermore, equation 5 implies that the penetration depth goes toinfinity at the cut-off point on the side of the film that has thebigger refractive index, which the penetration depth will be finite onthe other side. The d_(eff) will be also infinite in this case.

Again, the exponentially decaying evanescent field from lightpropagating in waveguide sensors only penetrates the cover medium to adepth of 50-200 nm with high intensity, when the waveguide gratingbiosensors fall into the conventional waveguide configuration. Thisvalue is dependent upon the refractive indices of the media present atthe interface, the illumination wavelength as well as the gratingstructure. When the incident angle equals the critical value, d_(c) goesto infinity, and the wavefronts of refracted light are normal to thesurface.

Considering a four-layer waveguide with following parameters: n_(F)=2.37(Nb₂O₅ layer), n_(s)=1.51 (1737 glass), n_(c)=1.333 (aqueous solution),n_(A)=1.37 (cells), d_(A)=500 nm (average thickness of cultured cells),d_(F)=157 nm, wavelength 830 nm, grating period 530 nm, we have: (1) Thecut-off thickness is 27 nm for TE₀ mode and 69 nm for TM₀, and 252 nmfor TE₁ mode and 294 nm for TM₁ mode, suggesting that this sensor onlysupports TE₀ and TM₀ mode. (2) The penetration depth is 78 nm for TE₀mode, and 112 nm for TM₀ mode. This means that (1) only the bottomportion of the adlayer of cells we was monitored, as highlighted in FIG.2 a by the broken arrow inside the cell; (2) target or complex ofcertain mass contributes more to the overall response when the target orcomplex is closer to the sensor surface as compared to when it isfurther from the sensor surface, as shown in FIG. 4. FIG. 4 shows theintensity of the evanescent wave penetrated into the medium decaysexponentially with increasing distance. Because of its highersensitivity, the TM₀ was used in most of exemplary studies in thepresent application unless specified.

(2) Reverse Symmetry Waveguide Grating biosensors

In the abovementioned waveguide sensors with conventionalconfigurations, the substrate refractive index (e.g, glass substrate,typically n_(s)˜1.5) is always higher than the aqueous cover mediumrefractive index (typically 1.33). The exponentially decaying evanescentfield from light propagating in such symmetry waveguide sensors onlypenetrates the cover medium to a short depth (typically ˜50-200 nm). Theevanescent tail on the substrate side is much longer and more intensethan on the cover medium side. This limits the response to analytes, asthe sensitivity depends on the fraction of the mode power propagating inthe analyte adlayer. Reversal of the mode profile would overcome thislimitation and permit larger (longer) penetration depths, therebyallowing analysis of morphology or intracellular components. Horvath etal. (US20030109055A1 and Horvath, R., Lindvold, L. R., and Larsen, N. B.“Demonstration of Reverse Symmetry Waveguide Sensing in AqueousSolutions,”, Applied Physics B, 2002, 74, 383-393; references thereinare incorporated) have demonstrated the feasibility of so-called reversesymmetry waveguides. The principle of reverse symmetry waveguide isbased on making the refractive index of the waveguide substrate lessthan the refractive index of the medium covering the waveguiding film(i.e., typically 1.33 for aqueous solution), as shown in FIG. 2 a. Asshown in FIG. 5, the reverse symmetry can be realized by three differentgeometries: (1) thin waveguide film deposited on a microstructuredsupport; (2) thin waveguide film deposited on a mesoporous or nanoporoussupport in which the refractive index of such nanoporous substrates isaround 1.15; and thin waveguide film deposited on nanostructuredsupport. By using such reverse configurations, the cover mediumpenetration depth significantly exceeds that of the conventionalwaveguide, when film thickness approaches the cut-off thickness of thetwo waveguides. Furthermore, by controlling the film thickness theprobing depth can also be controlled with no upper limit.

(3) Optical Detection Systems

In certain embodiments, the optical detection system can be eitherangular interrogation, or wavelength interrogation, or their variationsystems, for example, the arrayed angular interrogation system or thescanning wavelength interrogation system (U.S. patent application Ser.No. 10/993,565, filed Nov. 18, 2004 by N. Fontaine, et al. and “METHODFOR ELIMINATING CROSSTALK BETWEEN WAVEGUIDE GRATING-BASED BIOSENSORSLOCATED IN A MICROPLATE AND THE RESULTING MICROPLATE” by Y. Fang, etal., filed on Mar. 31, 2005 (Both of which are incorporated in theirentireties and at least for material related to biosensors, scanningdevices, and microplates), when optical waveguide biosensors are used.U.S. patent application Ser. No. 10/602,304, filed Jun. 24, 2003 havingpublication no. US-2004-0263841, published Dec. 30, 2004 and U.S.application Ser. No. 11/019,439, filed Dec. 21, 2004, and U.S. patentApp. for “OPTICAL INTERROGATION SYSTEM AND METHOD FOR 2-D SENSOR ARRAYS”by N. Fontaine, et al., filed on Mar. 31, 2005, all of which are hereinincorporated in their entireties by reference but at least forbiosensors and their uses.

Examples of a plate which can be used with a specific configuration ofthe OWG biosensor(s) in microplate is a 96 well Corning's Epic biosensormicroplate in which each well contains an optical waveguide grating(OWG) biosensor embedded in the bottom surface of a glass supportsubstrate.

Because the evanescent field of the guided mode projects into the coverliquid, the waveguide mode is exquisitely sensitive to the coverenvironment. When cellular events occur at the waveguide surface (e.g.,controlled releasing of biological materials from permeabilized cells),the resulted change the effective index of the cover medium because ofthe loss of mass, the propagation constant of the waveguide mode mustalso change in accordance with Maxwell's electromagnetic equations. As aresult of the phase-matching condition for the waveguide gratingstructure mentioned above, the preferred coupling angle (or wavelength)of input light must change in accordance with the waveguide propagationconstant change. These macroscopic physical changes can be monitored toindicate the microscopic cellular event.

b) Optical Waveguide Lightmode Spectroscopy (OWLS) Theory

Grating coupler biosensors are evanescent-wave sensors based on theresonant coupling of light into a waveguide by means of a diffractiongrating. The guided modes propagate in the planar waveguide by totalinternal reflection which can be described by the zigzag wave model.After having passed a full zigzag, the phase difference between theordinary wave and the twice-reflected wave is a function of the χcomponent of the wave-vector of the light in the film (β) only for agiven waveguide structure and fixed polarization and wavelength.Determined by self-consistency criteria, the value of P can becalculated numerically from the mode equation (Horvath, R., et al.,“Effect of Patterns and Inhomogeneities on the Surface of WaveguidesUsed for Optical Waveguide Lightmode Spectroscopy Applications,” Appl.Phys. B. 72, 441-447):

$\begin{matrix}{{\pi \; m} \cong {{d_{F}\left( {{k^{2}n_{F}^{2}} - \beta^{2}} \right)}^{0.5} - {\arctan \left\lbrack {\left( \frac{n_{F}}{n_{S}} \right)^{2\rho}\left( \frac{\beta^{2} - {k^{2}n_{S}^{2}}}{{k^{2}n_{F}^{2}} - \beta^{2}} \right)^{0.5}} \right\rbrack} - {\arctan \left\lbrack {\left( \frac{n_{F}}{n_{C}} \right)^{2\rho}\left( \frac{\beta^{2} - {k^{2}n_{C}^{2}}}{{k^{2}n_{F}^{2}} - \beta^{2}} \right)^{0.5}} \right\rbrack}}} & (7)\end{matrix}$

Here k=2π/λ, where λ is the vacuum wavelength of the guided light. ρ isa mode type number which equals 1 for TE and 0 for TM modes. n_(F),n_(s) and n_(c) are the refractive indices of the film, substrate andcover medium, respectively. The mode propagation direction in thewaveguide is χ, and m=0, 1, 2 . . . is the mode index of mth-guide mode.In the zigzag wave model, each ray represents a plane wave (P. K. Tien.,“Integrated Optics and New Wave Phenomena in Optical Waveguides,” Rev.Mod. Phys. 1977, 49, 361). If the light is coupled into the waveguide,it is only necessary to consider the coupling at those points where thezigzag wave strikes the film surface, and at these points simple rayoptics can be used.

As shown in FIG. 3, provided that the phase shift during one zigzag isΦ(β), the amplitude of the wave after the nth zigzag, (A_(n)(β)), willbe given by a geometrical series:

$\begin{matrix}\begin{matrix}{{A_{n}(\beta)} = {{A_{0}(\beta)}{\sum\limits_{j = 0}^{n - 1}^{{j}\; {\Phi {(\beta)}}}}}} \\{= {{A_{0}(\beta)}{G(\beta)}}}\end{matrix} & (8)\end{matrix}$

Here i denotes the imaginary unit, and

$\begin{matrix}{{{G(\beta)} = \frac{^{\; n\; {\Phi {(\beta)}}} - 1}{^{{\Phi}{(\beta)}} - 1}}{and}} & (9) \\{{{\Phi \left( \beta_{m} \right)} = {2\pi \; m}},{m = 0},1,{2\mspace{14mu} \ldots}} & (10)\end{matrix}$

Assuming that the whole grating length is illuminated, the couplinglength L equals the grating length, the total number, n, of the fullzigzags can be calculated:

$\begin{matrix}{n = \frac{L\sqrt{{k^{2}n_{F}^{2}} - \beta^{2}}}{2d_{F}\beta}} & (11)\end{matrix}$

Illuminating the grating at angle α_(o), the waveguide mode with β₀ isgenerated:

β₀ =kn _(air) sin(α₀)+2π/Λ  (12)

Where n_(air) is the refractive index of the air and Λ is the gratingperiodicity. Because of the finite width of the grating and laser beam,when illuminating the grating under angle α_(o) with a plane wave, thediffracted light can be described using a plane wave distribution. Thisleads to a peak at β_(o) with a Peak Width at Half Maximum (PWHM) ofapproximately 2π/L, calculated from the optical uncertainty principle(Tiefenthaler, K. and Lukosz, W, J., “Sensitivity of grating couplers asintegrated-optical chemical sensors”, J. Opt. Soc. Am. B. 1989, 6,209-220).

The intensity of the coupled light after the nth section (I_(n)(β)) isproportional to the absolute square of the amplitude of the light:|G(β)|²=IG(β). The relation between the coupled light intensity, I(α),and the incident angle, which can also be measured using opticalwaveguide lightmode spectroscopy (OWLS) technique, can be calculatedusing following equation:

I(α)=∫_(d)(β,α)IG(β)dβ  (13)

Where I_(d)(β,α) is the intensity distribution of the first-orderdiffraction:

$\begin{matrix}{{I_{d}\left( {\beta,\alpha} \right)} = {\frac{\sin \left( {{0.5L\; \beta} - {0.5{L\left( {{{kn}_{air}{\sin (\alpha)}} + \frac{2\pi}{\Lambda}} \right)}}} \right)}{\beta - \left( {{{kn}_{air}{\sin (\alpha)}} + \frac{2\pi}{\Lambda}} \right)}}^{2}} & (14)\end{matrix}$

c) Vertical Mass Redistribution and Lateral Mass Redistribution

Living cells are highly dynamic and most organelles travel extensivelywithin cells, for example, in response to activation of signalingmolecules or pathways. For example, microtubules can transportorganelles over long distances. A stimulus can result in the submicronmovement of densely packed organelles in the very periphery of a sensorsurface on which the cells are cultured; such movement leads to massredistribution within the cell. Such movements in response to signalsimulation can be called “trafficking” or “translocation” or“redistribution”. Such a trafficking or translocation or redistributionevent is generally associated with mass redistribution. The massredistribution can be detected by optical biosensors; and the signalrelating to mass redistribution is referred to as directional massredistribution (DMR) signal.

Since stimulation could lead to dynamic redistribution of cellularcontents in three-dimension, monitoring the cell responses with thechanges in incident angle or wavelength may not be sufficient for cellsensing with the biosensors. To simplify the analysis, the dynamic massredistribution can be divided into two types: vertical massredistribution which occurs perpendicular to the sensor surface, andlateral or horizontal mass redistribution that occurs parallel to thesensor surface. It is understood that a specific stimulatory event mayresult in one of these mass redistribution or the other, or both.

As implicated by the dynamic changes in the incident angle or resonantwavelength, the DMR signal is primarily resulted from the redistributionof cellular contents that occurs perpendicular to the sensor surface,since the biosensors are mostly sensitive to the mass redistributionparallel to the direction of the evanescent wave of the sensors. SuchDMR is also referred to vertical mass redistribution. Specifically, astimulatory event-induced mass redistribution in the direction that isparallel to the sensor surface and perpendicular to the direction of theevanescent wave of the sensors can lead to the change in homogeneity ofthe mass within the cell layer, and thus result in a change in theresonant peak, a resonant band image, and/or the OWLS spectrum. Suchchange(s) can be detected and used as signature for the effect ofstimulatory events or compounds on the stimulatory event-induced cellresponses. Such mass redistribution is referred to lateral massredistribution.

As shown in FIGS. 2 and 3, cells are directly cultured onto the surfaceof a resonant waveguide grating (RWG) biosensor. Exogenous signalsmediate the activation of specific cell signaling, in many casesresulting in dynamic redistribution of cellular contents, equivalent todynamic mass redistribution. When occurring within the sensing volume(i.e., penetration depth of the evanescent wave), the DMR can bemanifested and thus monitored in real time by a RWG biosensor—a labelfree technology that is sensitive to change in local refractive index inthe vicinity of the sensor surface. Because of its ability formulti-parameter measurements, the biosensor has potentials to providehigh information content for cell sensing. These parameters include theangular shift (one of the most common outputs), the intensity,peak-width-at-half-maximum (PWHM), and area of the resonant peaks. Inaddition, because of the unique design of our angular interrogationsystem which uses a light beam of ˜200 μm×3000 μm to illuminate eachsensor, the resonant band image of each sensor can provide additionaluseful information regarding to the uniformity of cell states (e.g.,density and adhesion degree) as well as the homogeneity of cellresponses for cells located at distinct locations across the entiresensor.

The RWG biosensor exploits the evanescent-wave that is generated by theresonant coupling of light into a waveguide via a diffraction grating.The guided light can be viewed as one or more mode(s) of light that allhave directions of propagation parallel with the waveguide, due to theconfinement by total internal reflection at the substrate-film andmedium-film interfaces. The waveguide has higher refractive index valuethan its surrounding media. Because the guided light mode has atransversal amplitude profile that covers all layers, the effectiverefractive index N of each mode is a weighed sum of the refractiveindices of all layers:

N=f _(N)(n _(F) ,n _(S) ,n _(C) ,n _(ad) ,d _(F) ,d _(ad) ,λ,m,σ)  (15)

Here, n_(F), n_(s), n_(c), and n _(ad) is refractive index of thewaveguide, the substrate, the cover medium, and the adlayer of cells,respectively. d_(F) and d_(ad) is the effective thickness of the film,and the cell layer, respectively. λ is the vacuum wavelength of thelight used. m=0, 1, 2, . . . is the mode number; and σ is the mode typenumber which equals to 1 for TE (transverse electric or s-polarized) and0 for TM modes (transverse magnetic or p-polarized).

Optical sensing of adherent cells is unique and quite challenging,because of the nature of cells interacting with surfaces and thecomplexity of cell structure and functions. Some types of cells areknown to be adherent on a surface, primarily through three types ofcontacts: focal contacts, close contacts and extracellular matrix (ECM)contacts. The focal contacts are narrow regions of an adherent cellmembrane (e.g., 0.2 μM×10 μm) that come within 10-15 nm of the substratesurface. The close contacts refer to regions of the cell membraneseparated from the substrate of 1-50 nm, whereas the ECM contactsdesignate regions of the cell membrane separated from the substrate by100 nm or more. Thus, one can appreciate that the sensor still is ableto sense the cover medium, even when the cell confluency is high (˜95%).However, it is known that living cells contain ˜70% water, and most ofintracellular bio-macromolecules are highly organized by the matrices offilament networks and spatially restricted to appropriate sites inmammalian cells. Furthermore, the height of the cells is typicallybeyond the wavelength of incident light (here λ=830 nm), while thepenetration depth is generally much smaller than the height of cells.Thus, the biosensor for cell sensing can be viewed as a three-layerconfiguration: the substrate, the waveguide, and the cell layer.

The value of effective refractive index N can be calculated numericallyfrom the mode equation for a given mode of a three-layer waveguide[Tiefenthaler, K., and W. Lukosz, “Sensitivity of grating couplers asintegrated optical chemical sensors” J. Opt. Soc. Am. B, 1989, 6,209-220]:

$\begin{matrix}{0 \cong {{\pi \; m} - {{kd}_{F}\left( {n_{F}^{2} - N^{2}} \right)} + {\arctan \left\lbrack {\left( \frac{n_{F}}{n_{S}} \right)^{2\sigma}\left( \frac{N^{2} - n_{S}^{2}}{n_{F}^{2} - N^{2}} \right)^{0.5}} \right\rbrack} + {\arctan \left\lbrack {\left( \frac{n_{F}}{n_{C}} \right)^{2\sigma}\left( \frac{N^{2} - n_{C}^{2}}{n_{F}^{2} - N^{2}} \right)^{0.5}} \right\rbrack}}} & (16)\end{matrix}$

Here, the wave vector k=2πm/λ.

The guided light modes propagate parallel to the surface of a planewaveguide, thus creating an electromagnetic field (i.e., an evanescentwave) extending into low-refractive index mediums surrounding both sidesof the film with a characteristic of exponential decaying. The amplitude(E_(m)) of the evanescent wave decays exponentially with increasingdistance z from the interface:

$\begin{matrix}{{{E_{m}(d)} = {{E_{m}(0)}{\exp \left( \frac{- z}{\Delta \; Z_{C}} \right)}}}{{with}:}} & (17) \\{{\Delta \; Z_{C}} = {\frac{1 - \sigma}{{k\left( {N^{2} - n_{C}^{2}} \right)}^{0.5}} + \frac{{\sigma \left\lbrack {\left( {N/n_{F}} \right)^{2} + \left( {N/n_{C}} \right)^{2} - 1} \right\rbrack}^{- 1}}{{k\left( {N^{2} - n_{C}^{2}} \right)}^{0.5}}}} & (18)\end{matrix}$

is the penetration depth of the evanescent tail of the waveguide modethat extends into the cover medium. Based on the configuration of thebiosensors used and the uniqueness of cell properties, the penetrationdepth of the TM₀ mode used here is 120 nm, meaning that we onlymonitored the bottom portion of the cells.

The translocation of proteins and/or molecular assemblies is common tomany cell responses triggered by exogenous signals. The translocationenables the precise control in the amplitude, duration and kinetics ofcell signaling through a specific target. In addition, in some casesexogenous stimuli could also cause changes in cell status such as theadhesion degree and cytoskeletal structure. When such changes occurwithin the sensing volume, the mode index N is altered due to theinteraction between the cover medium and the evanescent tail.

For the redistribution of cellular contents in a direction that isperpendicular to the sensor surface but parallel to the evanescent tailof the guided modes (referred to vertical mass redistribution), one candivide the bottom portion of adherent cells into multiple equal-spacedand homogenous thin layers, assuming that the degree and configurationsof adhesion are similar for cells being probed with the light beam at agiven time. Each layer has its own refractive index n_(i) and is awayfrom the sensor surface by a distance of z_(i) (FIG. 2 b). All layerscould be considered to have equal volume, because the unit area A isconsidered to be constant and determined by the spatial resolution ofthe optical biosensor which is limited to the physical size of incidentlight beam as well as the propagation length of the guided wave in thewaveguide. The refractive index of a given volume within cells islargely determined by the concentrations of bio-molecules, mainlyproteins [Beuthan J, O. Minet, J. Helfmann, M. Herrig, and G. Muller.1996. The spatial variation of the refractive index in biological cells.Phys. Med. Biol. 41:369-382):

n _(i) =n _(o) +αC _(i)  (19)

Here n_(o) is the index of the solvent, which is constant andapproximately equals to water in cells. α is the specific refractionincrement, and is about 0.0018 for protein, and 0.0016 for other solutesfound in cells such as sodium. C_(i) is the concentration of solutes (ing/100 ml) in the layer i. While the specific refraction increments aresimilar for proteins and other solutes, proteins primarily account forthe refractive index of each layer because their concentrations in termsof weight per volume are considerably greater than other solutes. Thus,the refractive index changes Δn_(i) of the homogeneous layer iapproximately form a piece-wise continuous function:

Δn _(i) =αΔC _(i)  (20)

The weighed index change Δn_(c) within the sensing volume is theintegration of Δn_(i) with a weighed factor exp(−z/ΔZ_(c)):

$\begin{matrix}{{\Delta \; n_{C}} = \frac{\int_{0}^{\infty}{\Delta \; {n(z)}^{(\frac{- z}{\Delta \; Z_{C}})}\ {z}}}{\int_{0}^{\infty}{^{(\frac{- z}{\Delta \; Z_{C}})}\ {z}}}} & (21)\end{matrix}$

Integrated from z=0 to z=∞, after substituting expression (7) for Δn(z)and rearrangement, we have:

$\begin{matrix}{{\Delta \; n_{C}} = {\alpha {\sum\limits_{i}{\Delta \; {C_{i}\left\lbrack {^{\frac{- z_{i}}{\Delta \; Z_{C}}} - ^{\frac{- z_{i + 1}}{\Delta \; Z_{C}}}} \right\rbrack}}}}} & (22)\end{matrix}$

Since in most cases Δn_(c) is a small portion of the refractive index ofthe cells sensed by the biosensors (generally less than 20%), thus tofirst order the change in effective refractive index is,

ΔN=S(C)Δn _(c)  (23)

where S(C) is the sensitivity to the cover medium (i.e., the cells):

$\begin{matrix}\begin{matrix}{{S(C)} = {{\partial N}/{\partial N_{c}}}} \\{= {{\frac{n_{C}}{N}\left\lbrack \frac{n_{F}^{2} - N^{2}}{n_{F}^{2} - n_{C}^{2}} \right\rbrack}{\frac{\Delta \; z_{C}}{d_{eff}}\left\lbrack {{2\frac{N^{2}}{n_{C}^{2}}} - 1} \right\rbrack}^{\sigma}}}\end{matrix} & (24)\end{matrix}$

with d_(eff) being the effective waveguide thickness given by:

$\begin{matrix}{d_{eff} = {d_{F} + {\sum{\Delta \; z_{C}}}}} & (25)\end{matrix}$

Inserting Eqs. 9 and 11 into Eq. 12, we obtain, for the detected signal:

$\begin{matrix}{{\Delta \; N} = {{\frac{n_{C}}{N}\left\lbrack \frac{n_{F}^{2} - N^{2}}{n_{F}^{2} - n_{C}^{2}} \right\rbrack}{\frac{\Delta \; z_{C}}{d_{eff}}\left\lbrack {{2\frac{N^{2}}{n_{C}^{2}}} - 1} \right\rbrack}^{\sigma}\alpha {\sum\limits_{i}{\Delta \; {C_{i}\left\lbrack {^{\frac{- Z_{i}}{\Delta \; Z_{C}}} - ^{\frac{- Z_{i + 1}}{\Delta \; Z_{C}}}} \right\rbrack}}}}} & (26)\end{matrix}$

The eq. 26 suggests: (i) changes of the effective refractive index, thusthe optical signature relating to the shift in the incident anglemeasured, is primarily sensitive to the vertical mass redistributionwithin the sensing volume; (ii) changes of the effective refractiveindex is directly a function of changes in protein concentration due toprotein relocation, rather than ion mobilization such as Ca²⁺ influx andCa²⁺ flux, mediated by a stimulation; (iii) the relocation of a targetor complex of certain mass towards the sensor surface contributes moreto the overall response than that moving away from the surface; (iv) theoptical signature is an integrated signal that is a sum of contributionsfrom mass redistribution occurring at different distances away from thesensor surface. Because of the complex nature of cell signaling, theactivation of distinct cell signaling mediated through different targetsmight result in similar overall DMR signal. However, because of theparticipation of unique sets of cellular targets for a specificsignaling event, the inhibition profiles mediated by a predetermined setof selective inhibitors might provide a means to classify thespecificity of cell signaling being activated by a particular stimulus.

As discussed above, the shift in the incident angle or resonantwavelength is largely determined by vertical mass redistribution withinthe sensing volume, when cells respond to stimulation. Because of thepoor lateral resolution of the biosensor, the lateral massredistribution may be difficult to be resolved by these shifts. However,because of the finite width of the grating and laser beam, thediffracted light can be described using a plane wave distribution whenilluminating the grating under angle α_(o) with a plane wave, asdiscussed in the RWLS theory section. This leads to a peak at β_(o) witha PWHM of approximately 2π/L, calculated from the optical uncertaintyprinciple, when no any adlayer exists. Modeling using these equationsled to interesting findings, which suggest that the shape of theresonant peaks (or spectra) carries valuable information about thelateral inhomogeneity of mass distribution. Such lateral inhomogeneitydoes not strongly perturb the cover medium refractive index, butsignificantly alters the shape of the resonant peaks.

It is well known that certain exogenous signals could lead tosignificant asymmetric lateral mass redistribution at the levels of bothsingle cell and multiple cells. For example, distinct populations ofcells could respond heterogeneously to compounds that are toxic tocells, while a single adherent cell could undergo uneven distribution ofcertain cellular targets or molecular assemblies during some cellularprocesses such as cell migration and invasion. We hypothesized that whenoccurring, the asymmetric lateral mass redistribution could also resultin the change in the fine structure and shape of the resonant peaks.

d) Dynamic Mass Redistribution in Cell Signaling and Cell Physiology

Living cells consist of a complex and dynamic network of proteinfilaments, termed as cytoskeleton which extends throughout the cytoplasmof eukaryotic cells. The cytoskeleton involves in executing diversecellular activities, for example, by providing tensile strength formaintaining cell shape, by providing the “track” or “docking sites” forsignaling and trafficking, and by providing force for cell motion,intracellular transport and cell division. There are three kinds ofcytoskeletal filaments: actin filaments, intermediate filaments andmicrotubules, each executing distinct biological functions. Among thesefilaments, actin filaments are mostly concentrated just beneath theplasma membrane, as they keep cellular shape, form cytoplasmaticprotuberancies, and participate in some cell-to-cell or cell-to-matrixjunctions, signal transduction and muscular contraction.

It is known that most of intracellular bio-macromolecules are highlyorganized by the matrices of filament networks and spatially restrictedto appropriate sites in mammalian cells. Furthermore, the localizationof cellular proteins is tightly controlled to regulate the specificityand efficiency of protein interactions, to spatially separate proteinactivation and deactivation mechanisms, and to determine specific cellfunctions and responses. In response to stimulation, there is often,sometimes significant, relocation of cellular proteins, depending on thenature of signaling pathway and its network interaction, cell status andthe cellular context. The relocation of proteins and molecularassemblies is fundamental not only to cell signaling by enabling precisecontrol in its amplitude, duration and kinetics, but also to cellfunctions such as migration, invasion, growth, cycling, differentiation,survival and death.

Perfect example is illustrated in G protein-coupled receptor (GPCR)signaling. GPCRs are a super family of membrane-bound proteins. Inunstimulated cells, endogenous GPCRs primarily locate at the cellsurface. After being exposed to ligands, cells respond with a series ofspatial and temporal events which are tightly and precisely controlledby intracellular signaling and regulatory machineries. These events leadto ordered, directed, directional and dynamic redistribution of cellularcontents during the GPCR signaling cycle. Monitoring the dynamicredistribution of cellular contents has provided insights into GPCRsignaling and a powerful means for GPCR screens. For example, directvisualization of the relocation of β2-adrenoceptor-GFP conjugates afteragonist stimulation initiated interest in this process as a directscreening strategy. One of these trafficking assays is the Transfluortechnology from Xsira Pharmaceuticals Inc (formerly Norak Biosciences).This technology employs high resolution fluorescence imaging to monitorthe intracellular location of fluorescently labeled arrestins inresponse to a compound. The re-localization of fluorescently labeledarrestins is viewed as an indication of agonism.

Many of these events occur within the bottom portion of the cells, whichcan be manifested by optical biosensors, resulting in an optical signalrelating to dynamic mass redistribution (DMR). The DMR signals act asnovel physiological responses of living cells. Theoretical analysisindicated that the optical signature, as indicated by the shift inincident angle or wavelength, is primarily sensitive to the verticalmass redistribution within the sensing volume (referred to DMR), whilethe optical output parameters relating to the shape (e.g.,peak-width-at-half-maximum, intensity, and area) of the resonant peakare sensitive to the stimulation-induced lateral mass redistribution.Because of the exponential decay of the evanescence wave tailpenetrating into the cell layer, a target or complex of certain masscontributes more to the overall response when the target or complex iscloser to the sensor surface as compared to when it is further from thesensor surface. Furthermore, the relocation of a target or complex ofcertain mass towards the sensor surface results in increase in signal,whereas the relocation of a target or complex moving away from thesurface leads to decrease in signal.

The DMR signals mediated through a particular target were found todepend on the cell status, such as degree of adhesion, and cell states(such as proliferating and quiescent state). Since the width or positionof the resonant peak of a sensor is sensitive to the cell density andviability, the biological status of cells (e.g., cell viability, celldensity, and degree of adhesion) that could significantly impact theassay results can be examined, resulting in reduced assay variability.

Three important aspects to qualify the suitability of a given approachfor systems biology applications are the ability of multiplexing, ofmulti-parameter analysis, and of quantitative system-response profiles.Since optical biosensors are label-free and non-invasive, thebiosensor-based cell assays are capable of multiplexing. For example,the agonist-induced activation of endogenous bradykinin B₂ receptor, P2Yreceptors, as well as protease activated receptors (PARs) in A431 hasbeen found to lead to similar Gq-type optical signatures (FIG. 66).Furthermore, since the optical biosensor offers an integrated response,the DMR signaling mediated through a particular target can also be usedto profile its downstream signaling target. For example, the EGF-inducedDMR in A431 can be used to profile the compounds that target one of itsdownstream targets: MEK1 (FIG. 44). These results suggested that thebiosensor-based cell assay is multiplexing in nature.

Optical biosensors offer multi-parameters to analyze the ligand-inducedDMR responses. These parameters include the shift in angle or wavelengthof the reflected light which is sensitive to the vertical massredistribution, and the parameters defining the shape of the resonantpeak which are mostly sensitive to the lateral mass redistribution. Thecombination of these parameters could further provide detailedinformation on the action of ligands on the cells examined (examples areshown in FIG. 80 for reactive oxygen species signaling, in FIG. 84 forEGFR signaling, and in FIG. 85 for bradykinin B₂ signaling).Alternatively, since the biosensor is non-invasive, the biosensor-basedcell assays can be easily integrated with other technologies, such asmass spectroscopy and fluorescence imaging. These technologies canfurther confirm the action of compounds or ligands on cells.

The DMR signal mediated through a particular target is an integrated andquantifiable signal that is a sum of contributions from massredistribution occurring at different distances away from the sensorsurface. Because of the complex nature of cell signaling, the activationof distinct cell signaling mediated through different targets mightresult in similar overall DMR signal. However, because of theparticipation of unique sets of cellular targets for a specificsignaling event, the modulation profiles mediated by a predetermined setof selective modulators might provide a means to classify thespecificity of cell signaling being activated by a particular stimulus.Therefore, the DMR response can be treated as a unique and perfectreadout for systems biology studies of living cells (examples are shownin FIGS. 38-47 for EGFR signaling; or in FIGS. 71-79 for PAR signalingin A431 cells). These studies showed that the modulations of differenttargets result in distinct attenuations of the DMR signal induced byEGF. In response to epidermal growth factor (EGF) stimulation, the DMRresponse of quiescent A431 cells was found to be saturable to theconcentration of EGF, and was able to be fully suppressed by a specificand potent EGFR tyrosine kinase inhibitor, AG1478. The effect of variousknown inhibitors/drugs on the DMR response of quiescent A431 cellslinked the cell response to mainly the Ras/mitogen-activated protein(MAP) kinase pathway, which primarily proceeds through MEK.

5. Cell Assays

Disclosed are the methods and uses of optical free biosensors to performany cell assay, such as an assay for cell death, an assay for cellproliferation, an assay for receptor activation or inhibition, an assayfor cell membrane integrity, an assay for lipid signaling, an assay forcell signaling, an assay for reactive species signaling, an assay forevaluating the redox states of cells, an assay for studycross-communication between distinct targets, an assay for highthroughput compound screening using endpoint measurements, and assaynuclear signaling or activity, or an assay for cytoskeletonrearrangement, for example. These assays incorporate the use of one ormore biosensor output parameters that can be used to produce a signaturefor the assay or which can be used to make a determination from theassay as well as one or more steps.

A biosensor can produce an output which can be in different forms, suchas pixels, or angular shift, or a wavelength shift, for example. Theoutput can be in the form of a output data which is output informationthat is collected for a particular set of conditions, and can either bestored or analyzed in realtime. A biosensor when used produces an outputof data, which typically can be represented in a graph form, such asresponse units versus time (see FIG. 6A as an example as well as manyother figures disclosed herein). The response unit can be angular shift(in terms of degree) when an angular interrogation detection system isused, or wavelength shift (in terms of pico-meters when a wavelengthinterrogation detection system is used), or pixel position shift (interms of pixel) when an angular interrogation detection system utilizinga CCD camera is used to collect the resonant band images of biosensors.Again, the response unit can be intensity of the incoupled light as afunction of incoupling angle (See FIG. 6B) or wavelength, when aresonant peak spectrum of a given mode is used. In another embodiment,the response unit can be position in pixel or positional intensity whenan angular interrogation detection system utilizing a CCD camera is usedto collect the resonant band images of biosensors (See FIG. 6C). Abiosensor output parameter or biosensor output data parameter is anycharacteristic of a biosensor output or output data respectively thatcan be measured and used to analyze the biosensor output or biosensoroutput data. In certain embodiments a biosensor output parameter canalso be a characteristic that can be identified and used across multipleassays. The signature is any biosensor output parameter or combinationof parameters that can be used as a diagnostic for a particular assay.For example, a signature could be the use of peak intensity magnitudeafter a stimulatory event, or it could be the position of the peakintensity after a stimulatory event, or it could be the position of thehalf maximal peak intensity. This signature can then be used to, forexample, compare the effect of two different compounds on a culture ofcells or the effect of a single compound on two different cultures ofcells, rather than a comparison of the entire data output. Thus, asignature could occur at a single time point or a single wavelength orsingle wave angle, or an any combination, depending on what is beassayed. (See discussions above for response unit)

a) Biosensor Output Parameters

A number of different biosensor output parameters that can be used areillustrated in FIG. 6. For example, six parameters defining the kineticsof the stimulation-induced directional mass redistribution within thecells can be overall dynamics (i.e., shape), phases of the response (inthis specific example, there are three main phases relating to the cellresponse: Positive-Directional Mass Redistribution (P-DMR) (FIG. 6Apoint C to D), net-zero Directional Mass Redistribution (net-zero DMR)(FIG. 6A point D to E) and Negative-Directional Mass Redistribution(N-DMR) (FIG. 6A point E to F to G)), kinetics, total duration time ofeach phase, total amplitudes of both P- and N-DMR phases, and transitiontime τ from the P— to N-DMR phase (FIG. 6A). Other biosensor outputparameters can be obtained from a resonant peak (FIG. 6B). For example,peak position, intensity, peak shape and peak width at half maximum(PWHM) can be used (FIG. 6B). Biosensor output parameters can also beobtained from the resonant band image of a biosensor. The data wasobtained using an arrayed angular interrogation system and illustrates 5five additional features: band shape, position, intensity, distributionand width. All of these parameters can be used independently or togetherfor any given application of any cell assays using biosensors asdisclosed herein. The use of the parameters in any subset or combinationcan produce a signature for a given assay or given variation on aparticular assay, such as a signature for a cell receptor assay, andthen a specific signature for an EGF receptor based assay.

(1) Parameters Related to the Kinetics of Stimulation-InducedDirectional Mass Redistribution

There are a number of biosensor output parameters that are related tothe kinetics of the stimulation-induced DMR. These parameters look atrates of change that occurs to biosensor data output as a stimulatoryevent to the cell occurs. A stimulatory event is any event that maychange the state of the cell, such as the addition of a molecule to theculture medium, the removal of a molecule from the culture medium, achange in temperature or a change in pH, or the introduction ofradiation to the cell, for example. A stimulatory event can produce astimulatory effect which is any effect, such as a directional massredistribution, on a cell that is produced by a stimulatory event. “Thestimulatory event could be a compound, a chemical, a biochemical, abiological, a polymer. The biochemical or biological could a peptide, asynthetic peptide or naturally occurring peptide. For example, manydifferent peptides act as signaling molecules, including theproinflammatory peptide bradykinin, the protease enzyme thrombin, andthe blood pressure regulating peptide angiotensin. While these threeproteins are distinct in their sequence and physiology, and act throughdifferent cell surface receptors, they share in a common class of cellsurface receptors called G-protein coupled receptors (GPCRs). Otherpolypeptide ligands of GPCRs include vasopressin, oxytocin,somatostatin, neuropeptide Y, GnRH, leutinizing hormone, folliclestimulating hormone, parathyroid hormone, orexins, urotensin II,endorphins, enkephalins, and many others. GPCRs are a broad and diversegene family that respond not only to peptide ligands but also smallmolecule neurotransmitters (acetylcholine, dopamine, serotonin andadrenaline), light, odorants, taste, lipids, nucleotides, and ions. Themain signaling mechanism used by GPCRs is to interact with G-proteinGTPase proteins coupled to downstream second messenger systems includingintracellular calcium release and cAMP production. The intracellularsignaling systems used by peptide GPCRs are similar to those used by allGPCRs, and are typically classified according to the G-protein theyinteract with and the second messenger system that is activated. ForGs-coupled GPCRs, activation of the G-protein Gs by receptor stimulatesthe downstream activation of adenylate cyclase and the production ofcyclic AMP, while Gi-coupled receptors inhibit cAMP production. One ofthe key results of cAMP production is activation of protein kinase A.Gq-coupled receptors stimulate phospholipase C, releasing IP3 anddiacylglycerol. IP3 binds to a receptor in the ER to cause the releaseof intracellular calcium, and the subsequent activation of proteinkinase C, calmodulin-dependent pathways. In addition to these secondmessenger signaling systems for GPCRs, GPCR pathways exhibit crosstalkwith other signaling pathways including tyrosine kinase growth factorreceptors and map kinase pathways. Transactivation of either receptortyrosine kinases like the EGF receptor or focal adhesion complexes canstimulate ras activation through the adaptor proteins Shc, Grb2 and Sos,and downstream Map kinases activating Erk1 and Erk2. Src kinases mayalso play an essential intermediary role in the activation of ras andmap kinase pathways by GPCRs.”

It is possible that some stimulatory events can occur but there is nochange in the data output. This situation is still a stimulatory eventbecause the conditions of the cell have changed in some way that couldhave caused a directional mass redistribution or a change in the cell orcell culture.

It is understood that a particular signature can be determined for anyassay or any cell condition as disclosed herein. There are numerous“signatures” disclosed herein for many different assays, but for anyassay performed herein, the “signature” of that assay can be determined.It is also possible that there can be more than one “signatures” for anygiven assay and each can be determined as described herein. Aftercollecting the biosensor output data and looking at one or moreparameters, or the signature for the given assay can be obtained. It maybe necessary to perform multiple experiments to identify the optimalsignature and it may be necessary to perform the experiments underdifferent conditions to find the optimal signature, but this can bedone. It is understood that any of the method disclosed herein can havethe step of “identifying” or “determining” or “providing”, for example,a signature added onto them.

(a) Overall Dynamics

One of the parameters that can be looked at is the overall dynamics ofthe data output. This overall dynamic parameter observes the completekinetic picture of the data collection. One aspect of the overalldynamics that can be observed is a change in the shape of the curveproduced by the data output over time. Thus the shape of the curveproduced by the data output can either be changed or stay steady uponthe occurrence of the stimulatory event. The direction of the changesindicates the overall mass distribution; for example, a positive-DMR(P-DMR) phase indicates the increased mass within the evanescent tail ofthe sensor; a net-zero DMR suggests that there is almost no net-changeof mass within the evanescent tail of the sensor, whereas a negative-DMRindicates a net-deceased mass within the evanescent tail of the sensor.The overall dynamics of a stimulation-induced cell response obtainedusing the optical biosensors can consist of a single phase (either P-DMRor N-DMR or net-zero-DMR), or two phases (e.g., the two phases could beany combinations of these three phases), or three phases, or multiplephases (e.g., more one P-DMR can be occurred during the time course).

(b) Phases of the Response

Another parameter that can observed as a function of time are the phasechanges that occur in the data output. A label free biosensor produces adata output that can be graphed which will produce a curve. This curvewill have transition points, for example, where the data turns from anincreasing state to a decreasing state or vice versa. These changes canbe called phase transitions and the time at which they occur and theshape that they take can be used, for example, as a biosensor outputparameter. For example, there can be a Positive-Directional MassRedistribution (P-DMR), a net-zero Directional Mass Redistribution(net-zero DMR) or a Negative-Directional Mass Redistribution (N-DMR).The amplitude of the P-DMR, N-DMR, and the NZ-DMR can be measured asseparate biosensor output parameters (See FIG. 6A and FIG. 7 forexample).

(c) Kinetics

Another biosensor output parameter can be the kinetics of any of theaspects of data output. For example, the rate at the completion of thephase transitions. For example, how fast are the phase transitionscompleted or how long does it take to complete data output. Anotherexample of the kinetics that can be measured would be the length of timefor which an overall phase of the data output takes. Another example isthe total duration of time of one or both of the P- and N-DMR phases.Another example is the rate or time in which it takes to acquire thetotal amplitudes of one or both of the P- and N-DMR phases. Anotherexample can be the transition time c from the P— to N-DMR phase (FIG.6A, as well as other figures provide many examples of all of these typesof kinetic parameters. The kinetics of both P-DMR and N-DMR events orphases can also be measured. For example, stimulation of human quiescenthuman epidermoid carcinoma A431 with epidermal growth factor (EGF)results in a dynamic response consisting of at least three phases, asshown in FIG. 6A and FIG. 7A. As evidenced in FIGS. 6A and 7, the higherthe EGF concentration is, the greater are the amplitudes of both theP-DMR and the N-DMR signals, the faster are both the P-DMR and the N-DMRevents, and the shorter is the transition time from the P-DMR to theN-DMR event. When the amplitudes of the P-DMR events showed acomplicated relationship with the EGF concentrations, the amplitudes ofthe N-DMR signals were clearly saturable to EGF concentrations,resulting in an EC₅₀ of ˜1.45 nM (See FIG. 7B). The transition time τ inseconds was found to decrease exponentially with the increasingconcentration C of EGF (See FIG. 7C). In addition, the decay of theN-DMR signal can be fitted with non-linear regression. The one-phasedecay constant K obtained was also saturable, resulting in a Kd of 5.76nM (see FIG. 7D).

(2) Parameters Related to the Resonant Peak

Resonant peaks of a given guided mode are a type of data output thatoccurs by looking at, for example, the intensity of the light vs theangle of coupling of the light into the biosensor or the intensity ofthe light versus the wavelength of coupled light into the biosensor. Theoptical waveguide lightmode spectrum is a type of data output thatoccurs by looking at the intensity of the light vs the angle of couplingof the light into the biosensor in a way that uses a broad range ofangles of light to illuminate the biosensor and monitors the intensityof incoupled intensity as a function of the angle. In this spectrum,multiple resonant peaks of multiple guided modes are co-occurred. Sincethe principal behind the resonant peaks and OWLS spectra is the same,one can use the resonant peak of a given guided mode or OWLS spectra ofmultiple guided modes interchangeably. In a biosensor, when either aparticular wavelength of light occurs or when the light is produced suchthat it hits the biosensor at a particular angle, the light emitted fromthe light source becomes coupled into the biosensor and this couplingincreases the signal that arises from the biosensor. This change inintensity as a function of coupling light angle or wavelength is calledthe resonant peak. (See FIG. 6B, for example). Distinct given modes ofthe sensor can give rise to similar resonant peaks with differentcharacteristics. There are a number of different parameters defining theresonant peak or resonant spectrum of a given mode that can be usedrelated to this peak to assess DMR or cellular effects. A subset ofthese are discussed below.

(a) Peak Position

When the data output is graphed the peak of the resonance peak occurs,for example, at either a particular wavelength of light or at aparticular angle of incidence for the light coupling into the biosensor.The angle or wavelength that this occurs at, the position, can changedue to the mass redistribution or cellular event(s) in response to astimulatory event. For example, in the presence of a potential growthfactor for a particular receptor, such as the EGF receptor, the positionof the resonant peak for the cultured cells can either increase ordecrease the angle of coupling or the wavelength of coupling which willresult in a change in the central position of the resonant peak. It isunderstood that the position of the peak intensity can be measured, andis a good point to measure, the position of any point along the resonantpeak can also be measured, such as the position at 75% peak intensity or50% peak intensity or 25% peak intensity, or 66% peak intensity or 45%peak intensity, for example (all levels from 1-100% of peak intensityare considered disclosed). However, when one uses a point other than thepeak intensity, there will always be a position before the peakintensity and a position after the peak intensity that will be at, forexample, 45% peak intensity. Thus, for any intensity, other than peakintensity, there will always be two positions within the peak where thatintensity will occur. The position of these non-peak intensities can beutilized as biosensor output parameters, but one simply needs to know ifthe position of the intensity is a pre-peak intensity or a post-peakintensity.

(b) Intensity

Just as the position of a particular intensity of a resonant peak canused as a biosensor output parameter, so to the amount of intensityitself can also be a biosensor output parameter. One particularlyrelevant intensity is the maximum intensity of the resonant peak of agiven mode. This magnitude of the maximum intensity, just like theposition, can change based on the presence of a stimulatory event thathas a particular effect on the cell or cell culture and this change canbe measured and used a signature. Just as with the resonant peakposition, the resonant peak intensity can also be measured at anyintensity or position within the peak. For example, one could use as abiosensor output parameter, an intensity that is 50% of maximumintensity or 30% of maximum intensity or 70% of maximum intensity or anypercent between 1% and 100% of maximum intensity. Likewise, as with theposition of the intensity, if an intensity other than the maximumintensity will be used, such as 45% maximum intensity, there will alwaysbe two positions within the resonant peak that have this intensity. Justas with the intensity position parameter, using a non-maximum intensitycan be done, one just must account for whether the intensity is apre-maximum intensity or a post-maximum intensity.

For example, the presence of both inhibitors and activators results inthe decrease in the peak width at half maximum (PWHM) after culture whenthe original cell confluency is around 50% (at 50% confluency, the cellson the sensor surface tend to lead to a maximum PWHM value); however,another biosensor output parameter, such as the total angular shift(i.e., the central position of the resonant peak) can be used todistinguish an inhibitors from an activators from a molecule having noeffect at all. The PWHM is length of a line drawn between the points ona peak that are at half of the maximum intensity (height) of the peak,as exampled in FIG. 6B. The inhibitors, for example, of cellproliferation, tend to give rise to angular shift smaller than the shiftfor cells with no treatment at all, whereas the activators tend to giverise to a bigger angular shift, as compared to the sensors having cellswithout any treatment at all, when the cell densities on all sensors areessentially identical or approximately the same. The potency or abilityof the compounds that either inhibit (as inhibitors) or stimulate (asactivator) cell proliferation can be determined by their effect on thePWHM value, given that the concentration of all compounds are the same.A predetermined value of the PWHM changes can be used to filter out theinhibitors or activators, in combination with the changes of the centralposition of the resonant peak. Depending on the interrogation systemused to detect the resonant peak of a given mode, the unit or value ofthe PWHM could be varied. For example, for an angular interrogationsystem, the unit can be degrees. The change in the PWHM of degrees couldbe 1 thousandths, 2 thousandths, 3 thousandths, 5 thousandths, 7thousandths, or 10 thousandths, for example.

(c) Peak Shape

Another biosensor output parameter that can be used is the overall peakshape, or the shape of the peak between or at certain intensities. Forexample, the shape of the peak at the half maximal peak intensity, orany other intensity (such as 30%, 40%, 70%, or 88%, or any percentbetween 20 and 100%) can be used as a biosensor output parameter. Theshape can be characterized by the area of the peak either below or abovea particular intensity. For example, at the half maximal peak intensitythere is a point that is pre-peak intensity and a point that ispost-peak intensity. A line can be drawn between these two points andthe area above this line within the resonant peak or the area below theline within the resonant peak can be determined and become a biosensoroutput parameter. It is understood that the integrated area of a givenpeak can also be used to analyze the effect of compounds acting oncells.

Another shape related biosensor output parameter can be the width of theresonant peak for a particular peak intensity. For example, at the widthof the resonant peak at the half maximal peak intensity (HMPW) can bedetermined by measuring the size of the line between the pre-peakintensity point on the resonant peak that is 50% of peak intensity andthe point on the line that is post-peak which is at 50% peak intensity.This measurement can then be used as a biosensor output parameter. It isunderstood that the width of the resonant peak can be determined in thisway for any intensity between 20 and 100% of peak intensity. (Examplesof this can be seen through out the figures, such as FIG. 6B).

(3) Parameters Related to the Resonant Band Image of a Biosensor

To date, most optical biosensors monitor the binding of target moleculesto the probe molecules immobilized on the sensor surface, or cellattachment or cell viability on the sensor surface one at a time. Forthe binding event or cell attachment or cell viability on multiplebiosensors, researchers generally monitor these events in atime-sequential manner. Therefore, direct comparison among differentsensors can be a challenge. Furthermore, these detection systems whetherit is wavelength or angular interrogation utilize a laser light of asmall spot (˜100-500 μm in diameter) to illuminate the sensor. Theresponses or resonant peaks represent an average of the cell responsesfrom the illuminating area. For a 96 well biosensor microplate (e.g.,Corning's Epic microplate), each RWG sensor is approximately 3×3 mm² andlies at the bottom of each well, whereas the sensor generally has adimension of 1×1 mm² for a 384 well microplate format. Therefore, theresponses obtained using the current sensor technology only represent asmall portion of the sensor surface. Ideally, a detection system shouldnot only allow one to simultaneously monitor the responses of live cellsadherent on multiple biosensors, but also allow signal interrogationfrom relatively large area or multiple areas of each sensor.

Resonant bands through an imaging optical interrogation system (e.g., aCCD camera) are a type of data output that occurs by looking at, forexample, the intensity of the reflected (i.e., outcoupled) light at thedefined location across a single sensor versus the physical position.Reflected light is directly related to incoupled light. Alternatively, aresonant band can be collected through a scanning interrogation systemin a way that uses a small laser spot to illuminate the sensor, and scanacross the whole sensor in one-dimension or two-dimension, and collectthe resonant peak of a given guided mode. The resonant peaks or thelight intensities as a function of position within the sensors can befinally reconsisted to form a resonant band of the sensor. In abiosensor, when either a particular wavelength of light occurs or whenthe light is produced such that it hits the biosensor at a particularangle, the outcoupled light varies as a function of the refractive indexchanges at/near the sensor surface and this changes lead to the shift ofthe characteristics of the resonant band of each sensor collected by theimaging system. Furthermore, the un-even attachment of the cells acrossthe entire sensor after cultured can be directly visualized using theresonant band (See the circled resonant band in FIG. 1, for example). Inan ideal multi-well biosensor microplate, the location of each sensor isrelative to normalize to other biosensors; i.e., the sensors are alignedthrough the center of each well across the row or the column in themicroplate. Therefore, the resonant band images obtained can be used asan internal reference regarding to the cell attachment or cellularchanges in response to the stimulation. Therefore, such resonant band ofeach sensor of a given mode provides additional parameters that can beused related to this band to assess DMR or cellular effects. A subset ofthese are discussed below.

(a) Band Shape

Another biosensor output parameter that can be used is the shape of theresonant band of each biosensor of a given mode. The shape is defined bythe intensity distribution across a large area of each sensor. As shownin FIG. 1 and others therein, the shape can be used as an indicator ofthe homogeneity of cells attached or cell changes in response tostimulation across the large area (for example, as shown in FIG. 1, eachresonant band represents responses across the entire sensor with adimension of ˜200 mm×3000 mm).

(b) Position

Similar to the position of the resonant peak of each sensor of a givenmode, the position of each resonant band can be used as a biosensoroutput parameter. The intensity can be quantified using imaging softwareto generate the center position with maximum intensity of each band.Such position can be used to examine the cellular changes in response tostimulation or compound treatment.

(c) Intensity

Just as the position of the resonant band, the intensity of theoutcoupled light collected using the imaging system can be used as abiosensor output parameter. The average intensity of the entire band orabsolute intensity of each pixel in the imaging band can be used toexamine the quality of the cell attachment and evaluate the cellularresponse.

(d) Distribution

The distribution of the outcoupled light with a defined angle orwavelength collected using the imaging system can be used as a biosensoroutput parameter. This parameter can be used to evaluate the surfaceproperties of the sensor itself when no cells or probe moleculesimmobilized, and to examine the quality of cell attachment across theilluminated area of the sensor surface. Again, this parameter can alsobe used for examining the uniformity of compound effect on the cellswhen the cell density across the entire area is identical; or forexamining the effect of the cell density on the compound-inducedcellular responses when the cell density is distinct one region fromothers across the illuminated area.

(e) Width

Just like the PWHM of a resonant peak of a given mode, the width of theresonant band obtained using the imaging system can be used as abiosensor output parameter. This parameter shares almost identicalfeatures, thus the useful information content, to those of the PWHMvalue of a resonant peak, except that one can obtain multiple bandwidths at multiple regions of the illuminated area of the sensor,instead of only one PWHM that is available for a resonant peak. Similarto other parameters obtained by the resonant band images, the width canbe used for the above mentioned applications.

All of these parameters can be used independently or together for anygiven application of any cell assays using biosensors as disclosedherein. The use of the parameters in any subset or combination canproduce a signature for a given assay or given variation on a particularassay, such as a signature for a cell receptor assay, and then aspecific signature for an EGF receptor based-assay.

b) Cells and Cell Context Manipulation

Cells are the fundamental structural unit of biological systems. Thus,understanding cells is essential for understanding both sub-cellularphenomena such as cell biology, biochemistry, and molecular biology andmulti-cellular phenomena such as physiology. By analyzing cells,biologists have learned many of the complex functional relationshipsamong distinct target molecules. The target molecules could be anybiological molecules, including DNA, RNA, lipid, protein, andcarbohydrate, among others, and among assemblies of such molecules.Furthermore, biologists have learned the value of using cells tounderstand basic cell biology principles and to screen drug candidatesfor treating human disease and improving human health.

Cells may be analyzed, or used for an analysis, using opticalbiosensors. Cells to be assayed may be essentially any type of cell. Anytype of cell can be assayed in any of the disclosed methods. Cells to beassayed can be either cells directly obtained from an organism or cellscultured in vitro. The cell having the target may be any cell from thegerm line or somatic, totipotent or pluripotent, dividing ornon-dividing, parenchyma or epithelium, immortalized or transformed, forexample. To date, there are wide arrays of immortalized stable celllines available. These stable cell lines are derived from many differentorganisms, tissues, and developmental stages. A sampling of this vastarray is available from American Type Culture Collection and other cellrepositories. Cells generally include any biological entity that is atleast partially bounded by a membrane bilayer and is capable ofreplication and division into two or more entities, or is a descendantof such an entity.

Examples of cells may include eukaryotic cells, i.e., cells with anucleus, including cells from animals, plants, fungi, yeast, andprotozoans; anucleate or mutant derivatives or descendants thereof, suchas reticulocytes and mature red blood cells, among others; enucleatedderivatives thereof; and fusions between any the preceding. In addition,cells may include gametes, such as eggs, sperm, and the like. Cells alsomay include prokaryotic organisms, such as bacteria and archactacteria.

Suitable cells may be derived from any suitable organism, including anyorganism that is studied for research (such as basic, clinical, andbiotechnology research, among others), drug design, drug discovery,and/or other economic, political, or humanitarian reasons. Exemplaryorganisms include mammals, such as apes, cats, cows, dogs, horses,humans, monkeys, mice, pigs, and sheep, among others. Exemplaryorganisms also include non-mammalian vertebrates, such as birds,reptiles, amphibians (e.g., frogs such as Xenopus laevis), and fish(e.g., kout, salmon, goldfish, and zebrafish), among others. Exemplaryorganisms also include nonmammalian invertebrates, such as species ofDrosophila (e.g., D. melanogaster and D. simulans), nematodes (e.g., C.elegans), sea urchins (e.g., Strongylocentrotus purpuratus), and slimemolds (e.g., Dictyostelium discoideum). Exemplary organisms also includesingle-celled eukaryotic organisms, such as yeast (e.g., Saccharomycescerevisiae, Schizosaccharomyces pombe, Pichia pastoris, and Candidaalbicans) and protozoans (e.g., pathogenic and nonpathogenicprotozoans). Exemplary organisms also include plants, such asArabidopsis thaliana, rice, corn, potato, bean, loblolly pine, as wellas nonvascular plants.

Suitable cells may be primary cells obtained directly from a wild-type,mutant, transgenic, chimeric zygote, morula, blastula, embryo, fetus,newborn, juvenile, adult, or other developmental stage of any organism.The primary cells may originate from distinct cell types, tissues,organs, or regions of the organism, or may be mixtures thereof. Examplesinclude blood stem cells, B- and T-lymphocytes, red blood cells,neutrophils, eosinophils, mast cells, granulocytes, megakaryocytes,macrophages, adipose cells, glial cells, astrocytes, neuroblasts,neurons, skeletal myoblasts or myotubes, smooth muscle myoblasts,cardiac myoblasts, fibroblasts, osteoblasts, osteocytes, endocrinecells, exocrine cells, endothelial cells, keratinocytes, chondrocytes,cells derived from endoderm, mesoderm, or ectoderm, and/orextraembryonic derivatives, such as trophoblasts.

Suitable cells may be obtained from a tissue or tissues from any source.Tissue generally comprises any group of cells in temporary or stablespatial proximity in an organism, or a cultured explant thereof. Thisspatial proximity may occur naturally and/or artificially and mayrepresent a native or normal state and/or an induced or diseased state,among others. Artificial proximity may include transplanted, implanted,and/or grafted tissue (including organ or tissue transplants,xenografts, allografts, and the like) and tissue moved within anindividual organism, such as a skin graft, among others. Diseased tissueincludes tissue that is abnormal due to a (1) genetic defect; (2) anenvironmental insult, such as a pollutant, a toxin, or radiation; (3)uncontrolled growth; (4) abnormal differentiation; (5) abnormal cellmigration; (6) infection, such as with a virus, bacteria, protozoan,yeast, fungus, and/or parasite; or (7) any combination thereof.

An exemplary diseased tissue suitable for use in the invention is tumormaterial obtained surgically or from a fluid aspirate, for example, froma needle biopsy. Tissue may be any tissue from any wild-type, mutant,transgenic, or chimeric zygote, morula, blastula, embryo, fetus,newborn, juvenile, adolescent, or adult organism. Examples of suitablepostnatal tissues include (1) muscle, including cardiac, smooth, andskeletal muscle; (2) neural tissue from the central or peripheralnervous system, such as spinal cord or brain; (3) other cardiac tissue;(4) kidney; (5) liver; (6) spleen; (7) any part of the digestive system,including esophagus, stomach, small and large intestines, and colon; (a)pancreas; (9) gall bladder; (10) circulatory system tissue, includingheart, veins and arteries, and cells of the hematopoietic system; (11)immune tissue, such as thymus and lymph nodes; (12) adrenal glands; (13)bone; (14) cartilage; and (15) any epithelial tissue, such as mammaryepithelium, among others. Tissue also includes natural and artificialcombinations of any of the above.

Tissue may be at least partially or completely disaggregated intoindividual cells before use with optical biosensors or may be applied tothe sensors whole or in sections.

Some applications of the invention are suited for clinical diagnosisusing cells derived from a prenatal or postnatal human or other animal.Examples of prenatal cells include those obtained from amniotic fluid, ablastomere, chorionic villi, fetal blood, and other fetal tissue.Examples of postnatal cells include those obtained from a bone marrowaspirate lymph, whole blood, blood serum, blood plasma, pleuraleffusion, skin biopsy, tumor biopsy, or a surgical procedure. Additionalexamples of postnatal cells include those obtained from other bodilyfluids and/or secretions, such as urine, feces, saliva, mucus, phlegm,tears, perspiration, semen, spinal fluid, milk, sputum, and the like, orfrom tissue, as described above.

Rather than from primary cells and tissue, or cultured derivativesthereof, suitable cells may be obtained from established cell lines.These established lines may be produced by any suitable method,including viral, oncogenic, physical, chemical, mutagenic, spontaneous,and/or kansgenic transformation. In addition, cells may includecharacterized or uncharacterized derivatives of established cell linesthat have been modified by any suitable method, such as geneticmodification (e.g., by physical and/or chemical treatment, irradiation,transaction, infection, or injection) and/or epigenetic modification(e.g., by methylation or other molecular modification, kansposonfunction, chromosome imprinting, yeast mating type switching, and/ortelomeric silencing).

The cell may be a stem cell or a differentiated cell. Cell types thatare, differentiated include adipocytes, fibroblasts, myocytes,cardiomyocytes, endothelium, neurons, glia, blood cells, megakaryocytes,lymphocytes, macrophages, neutrophils, eosinophils, basophils, mastcells, leukocytes, granulocytes, keratinocytes, chondrocytes,osteoblasts, osteoclasts, hepatocytes, and cells of the endocrine orexocrine glands. Stem cells may be stem cells recently obtained from adonor, and in certain preferred embodiments, the stem cells areautologous stem cells. Stem cells may also be from an established stemcell line that is propagated in vitro. Suitable stem cells includeembryonic stems and adult stem cells, whether totipotent, pluripotent,multipotent or of lesser developmental capacity. Stem cells arepreferably derived from mammals, such as rodents (e.g. mouse or rat),primates (e.g. monkeys, chimpanzees or humans), pigs, and ruminants(e.g. cows, sheep and goats).

Generally each cell line has distinct characteristics based on itsorigin, genotype, method of immortalization, culture conditions, andenvironmental history. Thus, no single cell line is suitable for allexperiments or compound screens. For example, the expression level of aparticular target could be distinctly different from one type of cell toanother type; in some cases, the signaling pathways through a particulartarget (e.g., EGFR) could significantly differ among different types ofcells. Therefore, a modulator that generates effect through a particulartarget could lead to dramatically different cellular responses includingmass redistribution are disclosed. For those reasons, a specific type ofcells may be required to be re-engineered such that a particular targetis controllably expressed or reduced or knockout, and in some cases, aparticular signaling pathway is manipulated. There are manystate-of-the-art technologies that can result in such re-engineeredcells. For example, with the help of transfection reagents or otherphysical approaches, transfection of cells with the target gene or thetarget molecules can result in the increasing expression level of thespecific target, whereas transfection of cells with an anti-targetantibody, or antisense, anti-target gene oligonucleotides and theirderivates, or peptide inhibitors, or interference RNA (RNAi) can lead tothe suppression of the target molecules. In addition, there is need fornew techniques for determination of cell signaling, or cellularresponses dependent on cellular context. The dependence of cellsignaling on the cellular context is perfectly exampled by receptortyrosine kinase signaling. The biological outcome of signals generatedat the cell surface in response to RTK stimulation is strongly dependenton cellular context. The same RTK will induce a totally differentresponse when expressed in different cells or at different stages ofdifferentiation of a particular cell lineage (see review in J.Schlessinger, “Cell signaling by receptor tyrosine kinases.” Cell 2000,103, 211-225). For instance, in early development, FGFR1 plays animportant role in control of cell migration, a process crucial formesodermal patterning and gastrulation. Stimulation of FGFR1 infibroblasts on the other hand, leads to cell proliferation whilestimulation of FGFR1 expressed in neuronal cells induces cell survivaland differentiation. The most plausible explanation for theseobservations is that different cells express cell type-specific effectorproteins and transcription factors that mediate the different responses.According to this view, RTKs and their signaling pathways are capable offeeding into multiple processes thus regulating the activity ofdifferent effector proteins and transcriptional factors in differentcellular environments. A similar input can therefore generate adifferent output in a different cellular context. In other words,signaling cassettes that are activated by RTKs have evolved in order torelay information from the cell surface to the nucleus and othercellular compartments of the biological outcome of their activation.

The term “incubating” includes exposing cells to any condition. While“culturing” cells is often intended to that permit one or more cells tolive and grow. Under certain conditions, incubating the cells under oneor more conditions may actually kill one or more cells.

c) General Method Steps

A general method for performing the cell assays disclosed herein can befound in FIG. 8. In this general method, one can provide a label freeoptical biosensor (801). Then cells are directly be cultured on thisbiosensor (802) to a desired confluency. (From 1% confluent to 100%confluent and each percentage in between). Then a buffer solution canoptionally be applied (803). Also a compound or compounds or compositionto be tested can be applied to the cultured cells on the biosensor. Thisis a stimulant event. (804). Then using any of the biosensor outputparameters described herein, the biosensor can be interrogated and thedata collected so that the cell responses to the stimulant event (504)can be monitored.

Generally disclosed are methods for performing living cell-based assaysusing label free biosensors, such as, an optical label independentdetection (LID) biosensor to monitor mass redistribution within livingcells adherent on a surface of the optical LID biosensor. In general,there are a number of different steps that can occur within thedisclosed methods. For example, the methods can comprise providing alabel free optical biosensor, such as an optical LID biosensor. Themethods generally also involve the culturing of cells on the biosensoras discussed herein. The culturing of the cells typically occurs in acell medium that can cover the optical biosensor. In certain embodimentsthe cells can attach to surface of the biosensor, much as they would toa culture dish, for example. When the cells are cultured on thebiosensor, they can be grown to any confluency as discussed herein, andthen various assays can be performed on the cells. For example, thecells can be incubated with a test compound or set of test compounds orcompositions, such as modulators, such as an agonist or antagonist of areceptor or an activator or repressor of a signal transduction pathwayor potential modulators, agonists, antagonists, activators, orsuppressors, to determine the effect of the compounds or compositions onthe cells or on a particular target within the cells. A modulator is anymolecule that either increases or decreases a particular event. Anagonist is a molecule such as a compound or composition, which effects areceptor in way and that is related to the way the natural ligandeffects the receptor. Typically this is to turn the receptor on oractivate it. An antagonist is a molecule, such as a compound orcomposition, which effects a receptor in a way that causes the effect ofthe natural ligand to be reduced or eliminated. Typically an antagonistis an inhibitor or repressor of a receptor. It is understood that someclasses of agonists can act in the absence of natural ligand or ligandanalog, while others function in the presence of the ligand or ligandanalog. For example, an antagonist could be a competitive inhibitor ofthe natural ligand or it could be a non-competitive inhibitor.

At any point, during the culturing of the cells, the cells can beassayed with the biosensor, wherein the biosensor is utilized, asdesigned, such as by providing light at a particular spectrum or at aparticular angle. The output from the biosensor can be collected in avariety of ways including time dependent ways. For example, the step ofinterrogating the optical LID biosensor to obtain a time dependentoptical response which indicates the mass redistribution within theliving cells that enables one to monitor an agonist-induced GPCRactivation within the living cells can be performed.

The step of applying a buffer solution at least once into the cellmedium located on the surface of the optical LID biosensor solution canalso be performed at any point during any of the methods. These bufferscan be applied to stabilize the medium or the biosensor or cells. Thebuffer used generally is chosen for achieving optimal assay resultsbased on the modulator-target interactions or stimulatory event-targetinteractions.

It is also understood that the methods can be used to screen formolecules that modulate (meaning either activate or suppress) a signaltransduction pathway, modulate a particular cell surface receptor, suchas a GPCR or an EGFR, within living cells.

It is also understood that in certain embodiments there can beincubation of more than one compound either in parallel or serially. Forexample, the biosensor-cell culture complex could be incubated with aknown modulator, such as an agonist or antagonist, which produces aparticular signature of a set of parameters, as discussed herein, andthen another compound(s) or composition(s) could be incubated with thebiosensor-cell-modulator mixture, and the effect of the compound on themodulator activity can be determined by looking for a change in thesignature or in the output of the biosensor generally afterinterrogation. It is understood that all of the steps related tocompounds or buffers can be done in increasing amounts to look at theeffect of the concentration of the compositions or composition has onthe biosensor output.

The methods can be performed with any biosensor as described herein, buta particular biosensor can be made into a self-referencing biosensor,which is a biosensor that is capable of not only collecting output datafor the cell assay, but it can also collect control data for the datacollected on the biosensor. This can be accomplished in a number ofways, including blocking a portion of the surface of the optical LIDbiosensor using a stamp that prevents attachment of the cultured cellsand then placing the living cells in a cell medium to cover an unblockedportion of the surface of the optical LID biosensor so the living cellsare able to attach to the unblocked portion of the surface of theoptical LID biosensor; and then removing the stamp from the surface ofthe optical LID biosensor.

The variation on the self referencing method can be to remove the stampafter the first culture of cells has adhered to the biosensor and thenplacing a second cell medium to produce a second cell culture on theposition of the biosensor that had been protected by the stamp. Thesecond cells can be a different type of cell, or different stage of cellof the same type, etc. but they the second cell is culturing independentof the first. It is understood that this can be performed as many timesas there are stamps. So for example, if there were four separate stampsthat had been used on the biosensor, then if each of these removedserially and another cell population was provided to the sensor, onewould culminate in 5 cultures of cells on the biosensor. Selfreferencing methods and systems allow for the reduction or eliminateunwanted sensitivity to ambient temperature, pressure fluctuations, andother environmental changes, and also provide confirmative informationregarding to a particular target or type of cells.

It is understood that not only can the effect of multiple compounds ondifferent types of cells be analyzed and the effect of a single compoundon different types of cells be analyzed, but cells having differentreceptors, for example, and how they are modulated and compare to oneanother can also be analyzed. This can also be multiplexed by providingdevices with multiple biosensors, such as a chamber having differentbiosensors.

It is also understood that, if for example, there are multiple differentreceptors on the different cells cultured on the biosensor, thatmolecules that are specific, such as specific antagonists could beprovided, and then, for example, a compound or compounds could betested. This type of method would provide information about whichreceptor antagonist, for example, was effected by which compound.

Disclosed are systems, comprising: an interrogation system; and anoptical label independent detection (LID) biosensor, wherein saidinterrogation system emits an optical beam to said optical LID biosensorand receives an optical beam from said optical LID biosensor whichenables said interrogation system to monitor mass redistribution withinliving cells located on a surface of the optical LID biosensor.

Also disclosed are systems, wherein said interrogation system is furthercapable of monitoring modulation of a cell, such as an agonist-inducedG-protein coupled receptor (GPCR) activation, within the living cellsafter the following steps are performed: providing the optical LIDbiosensor; placing the living cells in a cell medium to cover theoptical LID biosensor so the living cells are able to attach to thesurface of the optical LID biosensor; applying a solution containing acompound into the cell medium located on the surface of the optical LIDbiosensor; and interrogating the optical LID biosensor to obtain a timedependent optical response which indicates the mass redistributionwithin the living cells that enables one to monitor the massredistribution due to an agonist-induced GPCR activation within theliving cells. Also disclosed are systems where applying a buffersolution at least once into the cell medium located on the surface ofthe optical LID biosensor solution.

It is understood that any of the method steps discussed herein can beapplied to a system for performing the steps.

It is also understood that the optical output signals can be monitoredin real time, but at distinct time intervals (for example, 1 sec, 3 sec,5 sec, 10 sec, 15 sec, 30 sec, 60 sec, 2 min, 5 min, 10 min, 15 min, 30min, 60 min, 2 hrs, 5 hrs, 10 hrs, 24 hrs).

It is also understood that only two points during the assay are measuredbefore and after the compound addition to cells. The difference in termsof optical output parameters is analyzed.

d) Use of Biosensors for Cell Proliferation Assays

The characterizations of agents that either promote or retard cellproliferation are extremely important areas of cell biology anddrug-discovery research. Several approaches have been used in the past.Trypan blue staining is a simple way to evaluate cell membrane integritywhich is used as an indictor for cell survival, but the method requirescounting dead cells under a microscope and cannot be adapted forhigh-throughput screening. Many cell proliferation assays estimate thenumber of cells either by incorporating 3H-thymidine or5-bromo-2′-deoxyuridine (BrdU, a thymidine analog) into cells duringproliferation (i.e., cell division), or by measuring total nucleic acidor protein content of lysed cells. Incorporation of5-bromo-2′-deoxyuridine into newly synthesized DNA permits indirectdetection of rapidly proliferating cells with fluorescently labeledanti-BrdU antibodies or certain nucleic acid stains (such as Hoechst33342, TO-PRO-3 and LDS 751), thereby facilitating the identification ofcells that have progressed through the S-phase of the cell cycle duringthe BrdU labeling period. Another one of the most popular assays is MTTcell proliferation assay. The colorimetric MTT assay is based on theconversion of the yellow tetrazolium salt (MTT) to insoluble purpleformazan crystals due to the reduction by cellular mitochondrialdehydrogenases which only function in viable and metabolically activecells. After incubation of the cells with the MTT reagent forapproximately 2 to 4 hours, a detergent solution is added to lyse thecells and solubilize the colored formazan crystals. The samples are readat a wavelength of 570 nm using a plate reader. The amount of colorproduced is directly proportional to the number of viable cells.Expansion in the number of viable cells resulted in an increase in theactivity of the mitochondrial dehydrogenases, which leads to theincrease in the amount of formazan dye formed.

Previous types of assays are time-consuming because of the requirementof lengthy incubation steps. For example, many conventional BrdU-basedprotocols require DNA denaturation in order for the BrdU epitope tobecome accessible to the anti-BrdU antibody. The DNA denaturation istypically accomplished with heat (>90° C.) or acid (2-4 M HCl). Suchharsh treatments often make it difficult to perform multi-parameteranalysis because other cellular structures and antigens are not wellpreserved during these treatments. In addition, these conventionalassays may be useful for assaying certain cell types; and differenttypes of cells require different incubation protocols in order toachieve optimal assay results.

e) Characteristics for High Throughput Screening

Disclosed are methods that are suitable for high throughput screening ofcompounds that modulate or effect one or more signaling pathways in acell or cell proliferation or cell death. These high throughput methodsare based on the understanding that the biosensor output data can beassessed using a number of different parameters, as discussed herein.And that particular cells or particular receptors within cells orparticular cell events such as death or proliferation or modulation of asignaling pathway can have a particular signature, as discussed herein.This signature can be made up of one or more biosensor output parametersas discussed herein. Importantly for high throughput methods, it isimportant that the there be a time point during the method where thecollection of the biosensor output parameter data will be diagnostic ofthe state of the cell, i.e., a signaling pathway was activated ordeactivated or the cell has dies or the cell is proliferating. Thispoint can be where there is a combination of biosensor output parametersthat are used to define the signature.

The high throughput methods can be used in devices with, for example,devices that have many biosensors, such up to 49 wells, or 96 wells ormore. It is also understood that methods that can have a biosensoroutput parameter data collected within 1 hour, 30 min, 12 minutes, 11minutes, 10 minutes, 9 minutes, 8 minutes, 7 minutes, 6 minutes, 5minutes, 4 minutes, 3 minutes, 2 minutes, 1 minute, 59 seconds or ateach second down to 1 second of a stimulatory event for the cell cultureon the biosensor. It is also preferable that all of the collections forall of the biosensors, for example, complete plate of sensors, arecompleted in these times as well, but it is understood that this is notrequired.

Beside the characteristics associated with data collection duration andthe numbers of samples examined in parallel, the data analysis andintegrated presentations of the results that result in using the methodsand systems disclosed herein can be, for example, resonant band imagesand predetermined time points which can be collected and presented insite.

(1) Cell Confluency

For the methods, and in particular for high throughput screening, one ofthe critical parameters of the methods disclosed herein is the number ofstarting cells used. The number of starting cells should be in acritical range such that the resulted density of cells on the waveguidesubstrate under normal culture condition can allow one to examine achange in the number of cells, both an increase as well as a decrease.It is understood that the greater the cell density, the more of anoutput signal that will arise from the biosensor, because of the factthat the more cells that are on the plate, the more DMR events that arebeing measured at any given time, such as after a stimulatory event.Thus the number of cells can change for example the characteristics ofthe resonant peak (e.g., intensity, PWHM, shape and/or position), and/orthe features of the resonant band image (e.g., band shape, width,intensity, distribution, and/or position), and/or the amplitudes of theDMR event(s) (e.g., the P-DMR and/or the N-DMR). For example, theconfluency can be 30-100%, 30-70%, 40-60%, 45% to 55% or about 50%,however, the confluency can be any percent between 30 and 100%, such as38, or 57, or 63, or 88, or 75, or 95 or 99%. For differentapplications, the preferred confluency could be varied in order toachieve optimal performance. For example, for cell proliferation assays,in general, a preferred confluency is about 50%, but this can beslightly different for different cell types or different assays. Underthese conditions, the PWHM is around maximal for cells cultured undernormal conditions, so that modulators that interfere with cellproliferation can be evaluated in combination with theangular/wavelength shift or resonant peak/band position at the sametime, no matter whether the modulators are promoters or inhibitors forcell proliferation. Here both modulators result in a decrease in PWHM,but the promoters increase the angular shift while the inhibitorsdecrease the angular shift, compared to the cells without any treatment.For receptor assays or other applications relating to cell signaling andnetwork interactions, the confluency of cells could vary from 30% to˜99%, depending on the cell events to be monitored. For example, forcell apoptosis studies the cell confluency could be in the range of ˜10%to ˜99%. For GPCR screens or EGFR screens, the cell confluency ispreferably to be in the range of 50% to ˜99%.

(a) Interfere with Cell Proliferation

The present methods allow one to detect compounds that affect cellproliferation in a short time, such as within 60 seconds, 50 seconds, 40seconds, 30 seconds, 20 seconds, 10 seconds or at each second down to 1second for a complete plate of sensors. In one embodiment, disclosed aremethods for measuring the effect of compounds on cell proliferation,comprising: (a) providing a first and second optical-based label freebiosensor; (b) placing a cell of a given seeding numbers in a medium onto the first said sensor, such that after an optimal culturing undercell growth condition the cells attached reach an optimal confluency;(c) placing the same cell of the same seeding numbers in said medium inthe presence of a compound at a given concentration, (d) Culturing thecells under the same condition until the cell density of the said firstsensor reaches the optimal density; (e) collecting the optical outputparameters using an optical interrogation system. The optimal density ispreferably between 40%-70%; most preferably 45%-55%. The opticalinterrogation system is preferably a parallel interrogation system or ascanning interrogation system. Disclosed herein are compounds, eitherinhibitors or activators modify the proliferation rate of a given typeof cells, resulting in different number of cells attached onto thesensor substrate. The difference in density of attached cells gives riseto different optical waveguide lightmode spectra. Based on twoparameters, angular shift and the PWMH, one can distinguish inhibitorsversus activators.

f) Use of Biosensors for Cell Toxicity Screening

Drug discovery has become an industrialized process in which vastlibraries of compounds are screened for activity against a chosentarget. The wealth of active compounds that emerge from these primaryscreens has created a bottleneck in drug development. First-round hitsoften do not meet the safety and efficacy criteria required for humantherapeutics, so sequential rounds of optimization are required before aproduct can be administered to humans. Optimization requires assays thattest Absorption, Distribution, Metabolism, Elimination (Excretion), andToxicity (ADME/Tox). ADME/Tox screening, representing a $3 billionmarket today, in the drug discovery and development setting is takingcenter stage given the large fraction of lead compound and drug failuresassociated with toxicity properties. Thirty percent of the total newdrug attrition in the developmental pipeline is attributed to toxicityprofiles and side effects. ADME/Tox screening could have preventeddeaths caused by several drugs brought to the market or clinicalpractice (Zechnich, A. D. et al. (1994) West. J. Med. 160, 321-5). Thissurprising toxicity provides an excellent case study in light of thenumber of safe antihistamines currently on the market and the growinginterest among pharmaceutical scientists in early ADME/Tox screening.Given the large fraction of lead compound and drug failures associatedwith toxicity properties, ADME/Tox screening is taking center stage inthe drug discovery and development setting. The presumption thatchemical libraries contain compounds with a spectrum of positive andnegative effects forms the foundation of ADME/Tox screening. Beneficialfeatures of a drug candidate include high specificity, low toxicity,good oral absorption and half-life, among others. The goal of earlyhigh-throughput ADME/Tox screening is to distinguish between “good” and“bad” compounds, in terms of toxicity, early in the discovery process.The identification of problems early in drug screening represents thesingle largest cost-saving opportunity in the pharmaceutical industry atthe present time.

ADME/Tox screening is term that is generally used to describe theensemble of those tests that are used to characterize a compoundsproperties with respect to absorption by the intestine, distribution tothe organism, metabolism by the liver, excretion by the kidney, andtoxicity profiles. Traditionally, deployment of ADME/Tox approaches indrug development has occurred in the latter stages of drugdevelopment—essentially late in the process subsequent to the initialphases of discovery of “hit compounds.” Such a set-up was feasible whenthe number of drug discovery targets was few and the numbers ofhigh-throughput screening assay points were relatively low across thepharmaceutical enterprise. With the changing paradigm in the drugdiscovery space, the number of drug targets is expanding and so is thevolume of assay points performed in high-throughput screens. Therefore,it is imperative for the industry to quickly and efficiently triage, oridentify, “potential hits,” which might fail ADME and toxicityscreening. In this manner, ADME/Tox screening needs to be performedearlier in the process of drug discovery and development, e.g., primary(high-throughput screening) and secondary screening. Furthermore, anintegrated approach for predicting drug adsorption, toxicity andphysiological effects would greatly benefit drug discovery anddevelopment processes.

(1) Real-Time Monitoring Compound Adsorption, Distribution and Toxicity

ADME/Tox screening includes testing a compound's properties with respectto absorption by the intestine, distribution to the organism, metabolismby the liver, excretion by the kidney, and toxicity profiles.Information relating to compound adsorption and toxicity duringconventional HTS screening is generally discarded or missed; inaddition, the effect due to compound adsorption and toxicity complicatesdata analysis. The increasing use of high content screening technologystarts bridging toxicity screening with functional screening.

One aspect of the disclosed compositions, methods, and techniques is toeliminate the exiting gap between ADME/Tox screening and functionalscreening using cell-based assays in combination with label freeoptical-sensors.

In one embodiment, disclosed are methods for monitoring the compoundadsorption and toxicity in real time, comprising: (a) providing anoptical-based label free biosensor; (b) placing a cell in a medium,wherein the cell attaches onto the surface of the biosensor; (c)applying a solution containing a compound into the cell medium; (d) andmonitoring the response of the cells cultured on the biosensor. Thedisclosed methods can also be characterized by (c) Optionally applying abuffer solution at least once into the cell medium. Furthermore, thedisclosed methods can also incorporate more than one biosensor outputparameter as discussed herein in the analysis. In fact, methodsutilizing at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15,or more biosensor output parameters can be performed, and in certainembodiments it may be necessary to utilize more than one parameter toaccurately obtain a signature for the assay or cell condition, forexample. Also, in certain embodiments, the biosensor data outputparameter(s) used for the signature can occur in less than 1 hour, 50minutes, 40 minutes, 25 minutes, 10 minutes, 9 minutes, 8 minutes, 7minutes, 6 minutes, 5 minutes, 4 minutes, 3 minutes, 2 minutes, 1minute, 59 seconds or at each second down to 1 second after astimulatory event or biosensor data output collection.

g) Use of Biosensors for Monitoring Cell Activities

Disclosed are compositions, methods, and techniques, related to thefield of label free optical biosensors including waveguide grating-basedbiosensors. The compositions, methods, and techniques disclosed alsorelate to the field of cell-based assays. Because of the smallpenetration depth and the nature of the evanescent wave of the sensorsthat can be used, only the stimulation-induced DMR within the adlayer ofcells that occurs in the vicinity of the sensors surface leads to achange in effective refractive index, which, in turn, results in angleshift of the reflected light from the sensor. The angular shift can bemeasured to obtain the kinetics of the DMR response signal. In addition,because of that, distinct cellular responses would contributedifferently to the overall mass redistribution signals. For example,cell detachment from the extracellular matrices occurs at/near thesensor surface, and therefore can lead to significantly greaterresponses than those occurring inside the cells. Disclosed are methodsthat utilize optical biosensors to detect cell activities andcompound-/stimulus-induced cellular changes based on the massredistribution within the sensing volume of the sensors. For example,the disclosed compositions, methods, and techniques, relate to the useand the methods of use of optical-based biosensors for monitoring thebinding of ligands to receptor tyrosine kinases (RTKs) and thesequential signaling events including internalization of signals,movement of molecules or assemblies in cells in real time, and/orcytoskeleton re-arrangement and cell morphological changes. Disclosedare methods for screening compounds or modulators that can interferewith one of these signaling events in living cells.

The present invention uses optical-based biosensors including waveguidebased biosensors to monitor or investigate the binding of ligands toreceptor tyrosine kinases (RTKs), a family of cell surface receptor, andseveral sequential signaling events in living cells. Disclosed aremethods for screening compounds or modulators that could potentiallyinterfere with these signaling events, e.g., binding, sequentialphosphorylation, internalization/cytoskeleton rearrangement and celldeadhension. In another embodiment, disclosed are methods to confirm thephysiological or pharmacological effect of a compound against a specificreceptor in living cells.

Disclosed are real time and label free functional receptor tyrosinekinase cell-based assays for compound screening and profiling. Thedisclosed methods allow one to study the kinetics of three major eventsin the receptor signaling pathway simultaneously: ligand binding,phosphorylation, and internalization/cytoskeleton rearrangement. Thismethod according to the present invention also can be used to screen orclassify compounds that can interfere with these signaling events. Inagain another embodiment, disclosed are methods to screen modulators formultiple targets in the signaling pathways that interfere with the DMRsignal measured based on their unique characteristics, as defined by theoptical output parameters.

Computational models of the EGF receptor system have been very useful inunderstanding complex interactions between different parts of thereceptor pathway. However, there is only limited experimental dataavailable for direct measurements of the kinetics of these signaling andtrafficking in cells. Lacking the direct measurement of kinetics ofsignaling events limits the validation of these models. Therefore,methods and technologies that can simultaneously study the kinetics ofcell signaling events are needed to gain further understanding the EGFRsignaling.

(1) Mass Redistribution Monitoring

Disclosed herein, the adsorption, distribution and toxicity of acompound to a certain confluent cell layer near the cell-sensorinterface can be monitored in real time. Because of the intrinsiclimited-penetration sensing property (50-500 nM) (i.e., sensing volume)of optical-based biosensors, a mass redistribution that occurs withinthe volume where the sensor can sense results in a response change thatis observable as an angular or spectral change in the reflected beam.This sensor response may be recorded as a function of time as well assolution composition changes. In this manner, the kinetics of anystimulatory event or effect caused by a stimulatory event that leads toa mass redistribution within the sensing volume can be analyzed. Itshould be understood that the confluency of cells to be assayed isimportant for high sensitivity detection. The higher the sensitivityrequired the more important the confluency of the cells allows foroptimal detection as described here. The confluency of cells for massredistribution monitoring induced by stimulatory event is preferablywithin the range of 30-100%. Alternatively it may be at 70-99%.Disclosed methods for distinct applications (cell proliferation,compound toxicity, cell apoptosis, compound adsorption and metabolism,cell signaling pathway activation, cell morphological changes, celldeadhension and movement, receptor and target (molecules or molecularassemblies) activation and movement, etc) may require distinct cellconfluency (i.e., cell density) in order to achieve optimal assayresults. Again, different types of cells as well as differenttarget/signaling pathway activations might require different cellconfluency for optimal cellular responses and functions. It should beunderstood that such confluency is not intent to limit the assayprotocols or methods.

h) Cell Components and Biosensors

Biological cells, as shown in schematic drawing in FIG. 9, are complexstructures with components ranging in size from nanometers to tens ofmicrons. The cell, such as 1008 as shown in FIG. 10, typically has acytoplasm (typical range 5-30 μM) that contains numerous organelles.Typically, the largest organelle is the nucleus, whose size can rangebetween 3 and 10 μm. The nucleus contains DNA, RNA, proteins, andnucleic acid-protein complexes, such as DNA-protein or RNA-proteincomplexes. An important DNA-protein complex is chromatin. Mitochondriaare small organelles comprised of a series of folded membranes withsizes typically ranging from 0.5-1.5 μm. Other cell components includeendoplasmic reticulum (ER) (typically 0.2-1 μm), lysosomes (typically0.2-0.5 μm), peroxisomes (typically 0.2-0.5 μm), endosomes (typically100 nm), and gogli, for example. Living cells, such as 1008, are highlydynamic and most organelles travel extensively within cells. Forexample, microtubules can transport organelles over long distances. Astimulus can result in the submicron movement of densely packedorganelles in the very periphery of a sensor surface, such as 1010, onwhich the cells, such as 1008, are cultured; and such movement leads tomass redistribution, such as 1006, within the cell, such as 1008. Themass redistribution, such as 1006, can be detected by an opticalbiosensor, such as 1014; the signal relating to mass redistribution,such as 1006, is referred to as a directional mass redistribution (DMR)signal. Due to the limited range (˜tens to hundreds of nanometers) ofthe electromagnetic field propagating in the biosensors, such as theoptical LID sensor 1014, that can extend into the surrounding media(e.g, adherent cell 1008) as an evanescent electromagnetic field, incertain situations, only a fraction of the mass redistribution, such asin 1006, can be detected because the penetration depth is insufficientto penetrate all the way through the cell or cells, if in cell layers,for example. The distance the electromagnetic field can extend isreferred to as the penetration depth or sensing volume. In certainsituations only the lower portion of the adherent cells that are withina certain distance to the biosensor surface, such as 1010, can bedetected.

Cellular trafficking can occur, for example, when secretory organellesoccupy their docking site beneath the plasma membrane, and if endocyticvesicles at the plasma membrane reach their processing stations in thecytosol. In either direction, organelles must typically penetrate theso-called actin cortex beneath the plasma membrane, a dense meshwork ofactin filaments that is up to a few hundred nanometers thick. To theextent that actin filaments constantly assemble and disassemble, themeshwork is dynamic and permeable to organelles. Control mechanismsregulating the assembly and disassembly would also regulate thepermeability of the actin cortex.

Exocytic vesicles can insert receptors into the plasma membrane andrelease ligands into the extracellular space. Endocytic vesicles carryreceptors with bound ligand to internal processing stations. Caveolaeare plasma-membrane-associated vesicles with a presumed role in cellsignaling. Lipid rafts are thought to populate the plasma membrane assmall floating islands in which select membrane proteins meet in privateto exchange signals. Finally, there is the universe of membranereceptors, as disclosed herein. These can be embedded in large molecularcomplexes that continually recruit and release downstream effectormolecules.

Transport of cellular components or extracellular stimuli not onlyoccurs at the plasma membrane, but also occurs through signalingpathways within the cell and within multiple intracellular compartmentsand organelles. These events include (1) protein target or substraterecruitment to the nucleus, to the membrane, to the cytosol, throughoutrecycling pathways, to or from other organelles, uptake fromextracellular space (ligand binding, gene transfection, infection andprotein delivery); (2) redistribution of newly synthesized intracellularcomponents within various functional compartments at definedmicroenviroments and with mediated release locations. These cellularevents can lead to directional mass redistributions at certain timesduring signaling cycles.

(3). Multiple Penetration Depths for Cell Monitoring

Most or all of cell compartments are highly dynamic, and do their jobsin milliseconds to minutes and sometimes disperse soon thereafter. Toobserve signaling events mediated by single organelles and signalingcomplexes, traditionally in vivo methods are required to image singleorganelles, to detect molecules in small numbers and to report theirfunction at high resolution in time and space. Fluorescence microscopyis a natural choice so far as some organelles may be stainedspecifically with dyes, and more and more proteins have been conjugatedwith fluorescent proteins such as green fluorescent protein (GFP)without impairing their function. However, most plasma membrane eventsinvolve interactions with cytosolic proteins that have been recruited tothe plasma membrane transiently. Because even confocal microscopy looksinto cells to a depth of nearly half a micron when focused on the plasmamembrane, these and more conventional fluorescence microscopes showstrong ‘background’ fluorescence from the cytosol that obscures theweaker fluorescence from small structures or molecular assemblies nearthe plasma membrane.

Upon stimulation, live cells can undergo a great number of cellularevents, including but not limited to, ligand/compound binding to thereceptor or intracellular targets, movements and translocation ofcellular components, interaction of cellular signaling molecules,altered activities and even movement of cellular organelles or molecularassemblies, second messenger generation, cytoskeleton rearrangement andeven dramatically cell morphological changes. For example, GPCRsparticipate in a wide array of cell signaling pathways. Ligand bindinginitiates a series of intracellular and cellular signaling events,including receptor conformational changes, receptor oligomerization, Gprotein activation (GDP-GTP exchanges on G_(α) subunit, G_(α) and G_(βγ)disassociation, G protein decoupling from the receptor, generation ofG_(α)- and G_(βγ)-signaling complexes), and downstream signalingactivation that leads to second messenger generation (Ca²⁺ mobilization,inositoltriphosphate generation, and/or intracellular cAMP levelmodulation) and ultimately results in changes of specific geneexpression. Ligand-mediated GPCR activation also leads to thedesensitization of GPCRs from the cell surface and trafficking of manyintracellular proteins, as well as changes in phenotypes, morphology andphysical properties of the target cells. These changes could be static,long-lasting or dynamic (e.g., cycling or oscillation). Distinctsignaling events exhibit significantly different kinetics ranging frommilliseconds (e.g., GPCR conformational changes) to tens of seconds(e.g., Ca²⁺ flux) to even tens of minutes (e.g., gene expression, ormorphological changes). Although their characteristics (e.g., kinetics)are distinct, these events can lead to mass redistribution. Furthermore,the optical output parameters obtained using optical biosensorsgenerally represent the overall average of responses due to a greatnumber of cellular events, and distinct cellular events result indifferent contribution to the overall output parameters. The dependenceof the overall DMR responses of the cell on the penetration depth wouldbe extremely useful indicator where and when a DMR signal occurs.

As mentioned above, optical biosensors, depending on sensor structureand properties, give rise to a limited penetration depths into the covermedium (typically 50-500 nm), and can only detect the bottom part oftall cells (diameter of ˜10 microns) or bacteria (diameter of ˜1micron). Therefore, the measured quantity is mainly related to thecontact area between the organism and the surface, and near plasmamembrane area, and the morphological changes near the sensor surface. Inorder to probe the movement or activities of different compartments ororganelles inside cells which are far away from the plasma membranes, orrefractive index of the whole organism, one need extend the penetrationdepth to reach these changes. FIG. 11 shows the behavior of evanescentwave of the sensor that depends on the penetration depth. Thishighlights the importance of penetration depth on cell monitoring. Sincethe optical output signals or parameters are an intergrated andrepresentative readout of stimulation-induced cell responses, multipleevents such as receptor endocytosis or target complex movement or cellmorphological changes or cell deadhension or movement could makedistinct contributions to the overall responses obtained using opticalbiosensors. These events could occur at different locations relating tothe sensor surface. Therefore, by using multiple penetration depths formonitoring the cell responses induced by same stimulatory event, thecontributions of each event to the overall response and thus themechanism of cell responses can be understood.

Disclosed are methods that can be used to monitor the cellular DMRsignals in response to stimulation. In one embodiment, the methodsinvolve the different modes of the sensors to measure the overall DMRsignal of a particular type of cells in response to a specificstimulation. Different given modes of the sensors result in distinctpenetration depths with altered sensitivity (e.g., TM₀ mode tends togive rise to longer penetration depth, such as 120 nm for a givensensor, than TE₀ mode does, such as 90 nm for the same sensor. Inanother embodiment, disclosed methods can utilize at least twobiosensors with different waveguide and grating structure and propertiesthat result in different penetration depths for a given mode to measurethe overall DMR signals of cells. In another embodiment, disclosedmethods can use both conventional symmetry and reverse symmetrywaveguide grating biosensors to measure the overall DRM signals ofcells. The sensitivity of the trafficking signals or directional massredistribution (DMR) signals to the penetration depth can be used as asignature for identifying a particular cellular trafficking event. Thepresent methods that involve the modification of the biosensorconfiguration and structure, or “tuning” the penetration depths of aparticular waveguide sensor, provides useful means to monitor or detecta particular cellular trafficking event with high sensitivity andintracellular compartment specificity. Particularly the use of multiplesensors with different penetration depths can be used to depict thesignature of each cellular DMR or trafficking event. For a particulartrafficking or DMR event, the present invention allows one to measure ordetect the event with higher spatial resolution in Z-axis and highersensitivity.

(4). Multiplexed Cell Assays Using Optical Biosensors

Standard screening campaigns, assaying a single target at a time, havebeen successful for identifying potent drug candidates. However, verylittle information about compound selectivity is generated. Currently,selectivity studies are conducted downstream in the drug discoveryprocess; discarding compounds at this stage because of adverse bindingmakes the drug discovery process both expensive and time consuming.Multi-target screens that examine the activity of compounds againstmultiple targets in parallel are necessary to efficiently addresscompound selectivity early in the drug discovery process. Given theseconsiderations, together with the increasing pace of targetidentification and expansion of compound libraries, novel technologiesthat are amenable to multi-target screening are needed.

Disclosed are methods that can be used for multi-target and multi-cellscreening. In one embodiment, the present methods utilize the integratedoptical output parameters as a means for screening compounds againstmultiple classes of targets or multiple family members of same classtargets. For example, the activation of Ras/MAPK pathway in human A431cells through EGFR mediated by EGF leads to a unique DMR signature;multiple classes of targets including EGFR, Src kinase, MEK1/2,dynamine, and actin filaments play distinct roles in the overall DMRsignature. Again, in another example, in A431 cells, the activation ofRas/MAPK pathways can be mediated through several GPCR agonist-inducedEGPR transactivation, and result in similar DMR signature as EGF-inducedresponse; thus multiple family members of GPCR class targets can bescreened and examined.

In another embodiment, the present invention discloses a method thatsequentially cultures at least two types of cells onto distinct regionsof a single sensor, which can be used for multiplexed cell assays usingoptical biosensors. Cells can be distinct types of cells, orphysiological related, or disease related, or pathological related.Cells can also be originated from a same type of cells, one beingunmodified, and one being genetically or the like re-engineered, such asa knockout or suppressed or over-expressed a particular target ofinterest. For example, Chinese hamster ovary (CHO) cells and theirre-engineered CHO cells can be used. As shown in FIG. 12, a biosensor(1201) can be provided, and then a portion of this biosensor can bephysically blocked (1202) so that even if cells are placed on thebiosensor, the cells will not culture on this portion of the biosensor.One can then place a cell medium that has a cell type A and allow theseto grow on the unblock region (1203). Then the blocked region of thebiosensor can be unblocked and a second medium of cells of, for example,cell type B can applied such that cell type B becomes cultured on theregion that had been blocked (805). A solution can then be provided thatcontains a molecule capable of giving a stimulatory event (1206). Thebiosensor can then be operated such that data from the two regions, theinitial unblocked region and the region that had been blocked, can becollected and compared. The blocking can be achieved by placing a rubberstamp to cover a portion of the sensor, or by placing a cover platehaving a given number of posts or columns. The end of each post orcolumn can consist of an end made of soft materials such as rubber suchthat when the end of the column contacts with the part of the sensorsurface without damage or deterioration of the sensor properties. Thenumbers and locations of the posts or columns fit with the given formatof a sensor microplate. Alternatively, the blocking can be achieved byplacing a device into the sensor microplate such that each sensor can bedivided into at least two compartments. For example, the device can be acover plate having a given number of microcolumns; in the end of eachcolumn (or the whole column) there can be a thin (typically 1 mm) wallmade of flexible materials such as polymer. Once the column is placedinto each well, the bottom of the microcolumn contacts with the centerregion of a sensor, and both sides contact with the inner wall of eachwell. The cover plate preferably contains a given numbers of fluidchannels; each channel is associated with each microcolumn or the partof the microcolumn.

In again another embodiment, disclosed are methods that utilizephysically separated multiple biosensors, and each biosensor can be usedto host one type of cell. After initial cell attachment, a commonculture medium can be applied to the chamber that contains the multiplebiosensors. As shown in FIGS. 13 and 14, the method provides amodification of the disclosed methods related to the fact that thebiosensor is located in a specific spot of a chamber, such as a well ofmicrotiter plate. If a device is utilized that contains multiple wellmicroplate having multiple compartments within each well and eachcompartment has a biosensor, then different types of cells can be placedin each of the different chambers, allowing for analysis of a differentcell or set of conditions, for each well or biosensor (1302). Thenoptionally a common medium can be placed on each of the well to coverall biosensors or a different medium for each compartment can be appliedwith any combination between the two being disclosed (1303). Thesolution 1303, can contain a marker, such as a molecule that can createa stimulatory event, or a secondary solution can be applied containingone or more molecules for the stimulatory event (1304). The biosensor(s)can then be monitored and interrogated and the results from eachcompartment or sensor can be collected and compared (1305). In aparticular embodiment, the present invention presents a unique type ofbiosensor microplate, as shown as an example in FIG. 14, a opticalbiosensor-embedded multi-compartment and multi-well microplate whicheach well contains four compartments, each compartment can have onewaveguide grating substrate embedded. Each compartment can be used tohost a single type of cells. Four compartments can be separated by innerwalls, the height of the inner walls (preferably between 100 microns and2 millimeters) is typically much lower than those of each well (which isthe typical height of any given microplate), such that each well havingfour compartments can be used to examine simultaneously the effect ofone drug candidate on the multiple targets or multiple types of cells.The compartments within a well can be separated by a physical barriersuch that when a cell medium solution is applied to one compartment, andstays in the said compartment without cross-contamination with theadjacent compartments. It should be understood that the compartmentcould be 2, 3, 4, 5, 6 and more. Each well having a multicompartment canbe separated by a higher physical barrier, such as plastic wall of atypical microplate, such that a common solution with relative largevolume can be applied into each well to cover all compartments and usedfor a single assay.

In another embodiment, disclosed are methods that can utilize positionaland surface-mediated transfection to generate multiple types of cellswithin a single sensor or multiple sensors within a single chamber orwell. For a single sensor, a pre-determined region is chosen to depositmaterials such that once cells are cultured and attached, cells canuptake the materials and therefore result in a modified or re-engineeredcells, distinct from the original cells that culture and attach to theother regions without the deposited materials. The materials can bepreferably a target gene, or a antisense oligonucleotide and itsderivates, or a antigene oligonucleotide and its derivates, or aninterference RNA (single-stranded, or double stranded, or any kind), oran antibody, or a protein, or a protein domain, or a drug, or a peptide.For different kinds of materials to be delivered or uptaken by thecells, specific transfection reagents can be used to reach optimaleffect. Such methods or compositions can be achieved according asdescribed in US2004/0023391A1 and U.S. Pat. No. 6,544,790, which areherein incorporated in their entireties, but at least for materialrelated to methods for delivery to cells.

In another embodiment, disclosed are methods that can utilize positionaland surface-mediated transfection to generate multiple types of cellswithin a single sensor or multiple sensors within a single chamber orwell. For a single sensor, a pre-determined region is chosen to depositmaterials such that once cells are cultured and attached, cells canuptake the materials and therefore result in modified or re-engineeredcells, distinct from the original cells that culture and attach to theother regions without the deposited materials. The materials can bepreferably a target gene, or an antisense oligonucleotide and itsderivates, or a antigene oligonucleotide and its derivates, or aninterference RNA (single-stranded, or double stranded, or any kind), oran antibody, or a protein, or a protein domain, or a drug, or a peptide.For different kinds of materials to be delivered or uptaken by thecells, specific transfection reagents can be used to reach optimaleffect. Such methods or compositions can be achieved according asdescribed in US2004/0023391A1 and U.S. Pat. No. 6,544,790, which areherein incorporated in their entireties, but at least for materialrelated to methods for delivery to cells. The deposition of thematerials can be achieved using contact printing technologies (such aspin printing technologies), or stamping devices, or non-contact printingtechnologies such as dispenser devices or systems. For multi-biosensorswithin the same well separated by physical barriers, directly depositionof solution containing the materials can be achieved microplatedispenser. Such methods can be achieved according as described in, forexample, U.S. Pat. No. 5,807,522 A, U.S. Pat. No. 6,101,946 A, U.S. Pat.No. 5,731,152, U.S. Pat. No. 5,807,522, U.S. Pat. No. 5,601,980, U.S.Pat. No. 6,656,432 B1, EP0895082 B1 or U.S. Pat. No. 6,399,396 B1, whichare herein incorporated in their entireties, but at least for materialrelated to methods for delivery materials onto the surface of asubstrate.

In another embodiment, disclosed are methods that can use positionsolution transfection techniques for cells located at different sensorswithin a well and but separated by physical barriers. These methods canuse direct introduction of the materials mixed with transfection reagentinto each compartment wherein cells are pre-cultured and attached to thesensor. For example, a DNA-containing transfection reagent solution isadded into each compartment wherein cells have been placed onto thebottom substrate.

(5). Target Identification Using Optical Biosensors

Drug targets include mostly proteins that play a fundamental role in theon-set or progression of a particular disease. Until recently,pharmaceutical researchers have been limited to studying onlyapproximately 500 biological targets (Drews, J., “Drug Discovery: AHistorical Perspective” Science 2000, 287, 1960-1963). With thecompletion of the sequencing of the human genome, the number ofavailable and potential biological targets is being expanded vastly. Thenumbers of potential targets uncovered through genomics-based methodshave created an enormous need for target evaluation technologies.Traditional drug discovery methods, however, have and can address only alimited number of target families. This situation suggests that theconventional methods have become “boxed in.” That is, the methods areunable to create as rapidly the numbers of novel drugs (e.g., three tofive per year) that will be necessary to meet the business goals of themajor pharmaceutical companies. The traditional methods are unlikely toprovide breakthrough therapies for major diseases, such ascardiovascular diseases, neurodegenerative diseases, cancers, and type-2diabetes, or other largely unmet medical needs. For these reasons,target evaluation has become one of the fastest growing and mostcritical fields of genomic research. Establishment of a stronger linkbetween the target protein and the disease would lead to a lower failurerate when drugs proceed to clinical trials, and a shorter list oftargets that have been proven to be valuable as drug targets would leadto greater success. In addition, a more rapid means of achieving betterunderstanding of protein function would shorten the target evaluationprocess.

In drug discovery, target evaluation generally includes three major,critical stages: 1) target screening, 2) target identification, and 3)target validation. As the first and/or an early phase in targetevaluation, the target screening stage involves identifying moleculesthat may be associated with a disease process (e.g., up-regulation of aparticular gene identified through gene expression analysis). Targetidentification involves identifying molecules that clearly play a rolein a disease process. As such, this type of approach provides a greaterdegree of certainty, but a possibility still exists that the identifiedtargets will not be the best species or attach to the best binding sitesto interfere with a disease process, or they may not be “druggable,”meaning that the target is not suitable for drug target because it maynot play a dominant role in a disease or cancer, or modification of thetarget by a drug could lead to adverse side effects. If all issuccessful, one may proceed to target validation, which is the processof determining which among the selected molecules leads to a phenotypicchange when modulated, suggesting it may have value as a therapeutictarget.

In one embodiment, disclosed are methods that can be used for targetidentification and evaluation based on mass redistribution monitored byoptical biosensors. Mass redistribution, for example, associated withsignaling pathway activations, cell motility and morphological changescan be used as a signature for disease association of a particulartarget, since many of these changes involve in tumor progression andmigration. In one embodiment, the methods involve the comparison of theDMR responses of two types of cells mediated by a stimulatory eventthrough a particular target. As shown in FIG. 15, an optical biosensor(1501) can be provided. Then, a cell medium containing a particular typeof cell, cell A (1502) can be placed on the biosensor. Then a buffersolution (1503) can optionally be provided. A particular marker, whichis a stimulatory event, such as a modulator or potential modulator of aparticular pathway or receptor or cell can be added, for example in asolution (1504). The biosensor can then be used to monitor the cellresponse (1505). This same set of steps can be performed on a secondbiosensor (1506) and with a second cell type or cell culture (1507).After interrogation of the second biosensors (1510) the two responses(1505) and (1510) can be compared (1511).

FIG. 12 shows an alternative method for target identification andevaluation based on directional mass redistribution. A biosensor (1201)can be provided, and then a portion of this biosensor can be physicallyblocked (1202) so that even if cells are placed on the biosensor, thecells will not culture on this portion of the biosensor. One can thenplace a cell medium that has a cell type A and allow these to grow onthe unblock region (1203). Then optionally the blocked region of thebiosensor can be unblocked and a second medium of cells of, for example,cell type B such that cell type B becomes cultured on the region thathad been blocked (1205). A solution can then be provided that contains amolecule capable of giving a stimulatory event (1206). The biosensor canthen be operated such that data from the two regions, the initialunblocked region and the region that had been blocked, can be collectedand compared (1207).

FIG. 13 shows an alternative method for target identification andevaluation based on directional mass redistribution. FIG. 13 provides amodification of the disclosed methods related to the fact that thebiosensor is located in a specific spot of a chamber, such as a well ofmicrotiter plate. If a device is utilized that contains multiplechambers, and multiple biosensors are used, then different types ofcells can be placed on each of the different biosensors, allowing foranalysis of a different cell or set of conditions, for each chamber orbiosensor (1302). Then optionally a common medium can be placed on eachof the chambers to cover all biosensors or a different medium for eachchamber can be applied with any combination between the two beingdisclosed (1303). The solution 1303, can contain a marker, such as amolecule that can create a stimulatory event, or a secondary solutioncan be applied containing one or more molecules for the stimulatoryevent (1304). The biosensor(s) can then be monitored and interrogatedand the results from each collected and compared (1305).

Similar to that shown in FIG. 2 a, FIG. 10 provides a diagram that showsan exemplary label free biosensor along with the basic components. Theoptical LID system 1000 includes an interrogation system 1002 consistingof modules for controlling the light, electronics and other componentsfor data generation, collection and analysis, and an optical LIDbiosensor 1004 that can be used to detect and monitor a massredistribution. When the mass redistribution occurs aligned with thedirection of the evanescent wave of the sensor, a signal termed asdirectional mass redistribution is generated and can be collected andanalyzed. However, the mass redistribution occurs along or parallel tothe sensor surface might be also be detected by the optical biosensor,as indicated by a number of output parameters such as the PWHM, resonantband width and shape, etc. For example, a translocation of moleculessuch as GPCR 1020 or molecular assemblies could occur starting from thecell surface facing the sensor to intracellular compartments such asendosome or ER. Such movement, as seen in the arrow numbered 1006 withthe living cells 1008 (only one shown), generally leads to a decrease ofmass within the sensing volume of the sensors as defined by thepenetration depth. In a preferred embodiment, the interrogation system1002 interrogates the optical LID biosensor 1004 (e.g., SPR sensor 1004,waveguide grating sensor 1004) so it can detect and monitor the massredistribution within the living cell 1008. This can be done by emittingan optical beam 1012 which has the appropriate spectral or angularcontent as discussed herein, towards the optical LID biosensor 1004 suchthat when the optical beam 1012 is reflected by the sensing surface1010, the resonant angle or wavelength response which identifies themass redistribution becomes dominant in the reflected beam 1014. Thus,when there is a detectable mass redistribution within the living cell1008, the optical LID biosensor 1004 can sense a response change whichis observed as an angular or wavelength change in the reflected beam1014. The optical response may be recorded as a function of time. Inthis way, the kinetic biosensor output parameter, or any otherparameter, of any event that leads to a mass redistribution within theliving cell 1008 can be analyzed, as discussed herein.

Referring to FIG. 16, there is shown a diagram where the optical LIDsystem 1000 is used to monitor a stimulatory event, such as anagonist-induced translocation of G protein coupled receptors 1602 (GPCRs1602) within a living cell 1008 (only one shown) located on the topsurface 1010 of the optical LID biosensor 1014. In particular, thediagram illustrates an agonist induced and time-dependent opticalresponse 1601 that partly is due to the translocation of a target GPCR1602 within the living cell 1008. The cell is adherent on the topsurface 1010 of the waveguide-based biosensor 1014. For clarity, theinterrogation system 1002 is not shown in the portion labeled as “C”.

As can be seen, the GPCR 1602 in the resting state resides at the cellsurface 1604 (plasma membrane 1604), while the GPCR kinase 1606 (GRK1606) and arrestin 1608 are uniformly distributed inside the cytosol ofliving cell 1008 (see diagram “A”). Upon agonist activation, the GPCR1602 activates heterotrimeric G proteins composed of α, β, and γsubunits. The Gα and Gβγ subunits dissociate which causes the GRK 1606to be recruited to the receptor 1602 at the plasma membrane 1604. Then,the GRK 1606 phosphorylates the carboxy terminus of the GPCR 1602. And,β-arrestin 1608, a relatively abundant intracellular protein, rapidly(within minutes) translocates within the cytoplasm to the activated GPCR1602 at the plasma membrane 1604, binds the GRK-phosphorylated receptor,and uncouples the receptor from its cognate G protein. The β-arrestin1608 then binds to the desensitized GPCR 1602 and translocates toclathrin-coated pits at the cell surface 1604 where the receptor 1602 isinternalized in clathrin-coated vesicles (CCV) (see diagram “B”).Finally, the entire complex 1602 and 1606 is delivered to the endosome1610 (endocytic vesicle 1610) (see diagram “C”). This process is knownas translocation. For more information about GPCR translocation,reference is made to the following three articles: Pierce, K. L. et al.“Seven-transmembrane receptors.” Nat. Rev. Mol. Cell. Biol. 2002, 3,639-650, which are incorporated in their entireties at least formaterial related to translocation.

It should be appreciated that these translocation events lead todirectional mass distribution (e.g., towards the cell surface or leavingthe cell surface) within the living cells 1008 at a certain time,therefore resulting in different optical responses through a prolongperiod of time. Another possible biological event that can lead todirectional mass distribution is the cell morphological changes due tothe GPCR activation. The cell morphological changes involve thecytoskeleton rearrangement as well as cell adhesion changes.Cytoskeleton is a complex network of protein filaments that extendsthroughout the cytoplasm of eucaryotic cells and is involved inexecuting diverse activities in these cells. As well as providingtensile strength for the cells it also enables muscle contraction,carries out cellular movements and is involved in intracellularsignaling and trafficking, cell division and changes in the shape of acell. Activation of G-protein coupled receptors (GPCR) leads to at leasttwo independent events that theoretically could exert an effect on thecytoskeleton rearrangement. The first event is the activation of theintracellular signaling pathway, and the second is a receptor-mediatedendocytosis (i.e., translocation), which occurs after an agonistactivation of the majority of GPCR. Activation of an intracellularsignaling pathway after an agonist/GPCR binding then leads to twofurther sets of connected events. Processes in the first set lead to theactivation of a secondary intracellular signaling pathway (Gprotein→effector→message), while the mechanisms of the second setregulate the degree of signaling within the cell by affecting the eventsin the first set. These mechanisms includephosphorylation/desensitization, internalization and downregulation ofmembrane-bound receptors. It is assumed that both sets of events canlead to the rearrangement of actin filaments within the cell. Forexample, after the activation of GPCR, various forms of G proteins (e.g.G_(α) and G_(βγ)) can bind with F-actin filaments; and those and othersignaling molecules can disassociate from actin filaments. Theinternalization process of membrane-bound receptors that occurs viareceptor-mediated endocytosis could also be responsible for the dynamicsof actin filaments.

Referring again to FIG. 16 and in accordance with the present invention,the different states associated with GPCR translocation within a livingcell 1008 can be identified and monitored by analyzing the opticalresponse 1601 from the optical LID system 1000. In fact, three differentevents can be identified when looking at the optical response 1601 shownin FIG. 16. The three major events that can be seen include: (1) a verylarge and sharp decrease in signal 1601 upon the addition of agonist,due to bulk index of refraction changes (i.e., in this example thecompound solution has relatively lower refractive index than the cellmedium. Thus compound addition results in a decreased LID signal); (2) atransition stage which has slow changes in the response signal 1601 andlasts almost 20 minutes: this stage can be related to the cell signalingpathway activation including, but not limited to, the phosphorylation ofthe activated receptors 1602 by GRKs 1606, arrestin binding,desensitization of the receptors 1602 to chathrin-coated pits, and/orother cellular responses; and (3) a slow decrease of response signal1601 which lasts almost 50 minutes, corresponding to the translocationof the GPCR complexes 1602 and 1608 to the endosome 1602 or othercellular responses such as cytoskeleton rearrangement. In other cases,an additional event that immediately followed the initial step can beevident (e.g., FIG. 16); that is a rapid fluctuated response signal1601, mainly due to the introduction and/or diffusion of the compound inthe cell medium and/or recruitment of intracellular components toactivated GPCRs at the cell surface. Details about how this test can beperformed by the optical LID system 1002 are described below withrespect to method 1700 shown in FIG. 17.

FIG. 18 shows an example of target identification using DMR. In FIG. 18,no matter whether CHO cells were cultured in a medium containing 10%fatal bovine serum (FBS) (data not shown) or 0.1% FBS (at least 16hours) (1801), EGF stimulation did not result in significant DMRresponses, except for a rapid change in signal that lasts typically lessthan 20 sec right after the introduction of a 50 μl EGF solution intothe cell medium of 150 μl. This rapid change is due to a bulk indexchange. In contrast, when a stimulatory event occurs, such as theaddition of EGF, EGF-induced responses of A431 cells strongly depend onthe culture condition. EGF-treatment of A431 cells starved in 0.1% FBSfor 20 hours gave rise to a time-dependent response (1802) that consistsof three sequential phases, providing 3 biosensor output parameters: (i)a positive phase with increased signal (P-DMR) (Point C to D), (ii) anet-zero phase (Point D to E), and (iii) a decay phase with a decreasedsignal (N-DMR) (Point E to F to G), after the initial rapid phase ofbulk index changes. In contrast, proliferating A431 cells (10% FBS) onlygave rise to the P-DMR phase (1803), whereas A431 cells treated with0.1% FBS for only 4 hours gave rise to similar responses (1804) but withaltered kinetics and much smaller amplitudes, compared to thosequiescent A431 cells. These results suggest that one can identify orevaluate a target (e.g., EGFR) in a given type of cells based on amarker-induced DMR response, such as using an activator or inhibitor ofa cell signaling pathway (i.e., EGF in this particular sample).

i) Cell Signaling

Cell signaling can be monitored using the disclosed systems and methods.For example, referring to FIG. 17, there is shown a flowchartillustrating the basic steps of a method 1700 for monitoring in realtime the mass redistribution due to an agonist-induced GPCR activationwithin living cells 1008 using an optical LID biosensor 1004 inaccordance with the disclosed methods. The method 1700 includes thefollowing steps: (a) providing an optical LID biosensor 1004 (step1702); (b) placing a certain number of living cells 1008 in a mediumwhich covers the optical LID biosensor 1004 such that the living cells1008 attach onto the surface 1010 of the optical LID biosensor 1004(step 1704); (c) optionally applying a buffer solution at least onceinto the cell medium (step 1706); (d) applying a solution containing acompound (agonist) into the cell medium (step 1708); and (e)interrogating the optical LID biosensor 1004 and monitoring the timedependent optical response 1601 of the living cells 1008 cultured on theoptical LID biosensor 1004 (step 1710).

It should be appreciated that if step 1706 is performed and a buffersolution (the same buffer solution that is used to formulate thecompound of interest) is applied to the living cells 1008 beforeapplying the compound, any unwanted effect, due to the living cells 1008responding to the environmental changes, can be minimized. This ispossible because living cells 1008 that are cultured on the optical LIDbiosensor 1004 are alive and dynamic which means that they can sensechanges in the surrounding medium compositions as well as temperatureand can respond to those changes. However, as the living cells 1008sense changes like the addition of a buffer then they tend to becomeresistant to those changes in the medium composition assuming noadditional chemical is introduced.

It should also be appreciated that the real time method 1700 providesquantifiable information, and equally important, it provides thekinetics of the mass redistribution within cells due to GPCR activation.In contrast to traditional methods of screening GPCRs, this method 1700is simpler to perform, more sensitive, label-independent and isapplicable to all GPCRs 1002 without requiring prior knowledge ofnatural ligands or how a given receptor is coupled to downstreamsignaling pathways.

It should also be appreciated that in the step 1704 the number of cellsshould be optimized such that after a certain time cultured underoptimal conditions the cells become adherent and reach high confluency(optionally larger than 75%) on the surface 1010 of an optical LIDsensor 1004 in order to achieve high sensitivity.

Referring to FIG. 19, there is shown a flowchart illustrating the basicsteps of a method 1900 for screening an agonist against a target GPCR1002 based on mass redistribution within living cells 1008 using theoptical LID biosensor 1004 in accordance with the present invention. Themethod 1900 includes the following steps: (a) providing the optical LIDbiosensor 1004 (step 1902); (b) placing a certain number of living cells1008 in a medium which covers the optical LID biosensor 1004 such thatthe living cells 1008 attach onto the surface 1010 of the biosensor 1004(step 1904); (c) applying a solution containing an antagonist with aknown affinity at a certain concentration into the cell medium for acertain time until the optical LID biosensor 1004 becomes stabilized(step 1906); (d) applying a solution containing a compound (agonist)into the cell medium (step 1908) where the concentration of the compoundis sufficiently high to compete off the receptor-bound antagonist; and(e) interrogating the optical LID biosensor 1004 and monitor the timedependent optical response 1601 of the living cells 1008 cultured on theoptical LID biosensor 1004 (step 1910).

It should be appreciated that in this method 1900 by pre-applying theantagonist to one receptor in the living cells 1008, effectively enablesone to screen the compounds for their agonism against this particularreceptor. Moreover, it should be appreciated that this method 1900 issimilar to the previous method 1800 except for one difference in thatmethod 1900 requires pre-knowledge about the functionality of thecompound for its cognate receptor in the living cells 1008. Forinstance, one needs to know whether the antagonist inhibits theactivation of GPCR 1020, or whether the antagonist activates the GPCR1020 which leads to translocation.

Referring to FIG. 20, there is shown a flowchart illustrating the basicsteps of a method 2000 for screening an antagonist against a target GPCR1020 based on mass redistribution within living cells 1008 using theoptical LID biosensor 1004 in accordance with the present invention. Themethod 2000 includes the following steps: (a) providing an optical LIDbiosensor 1004 (step 2002); (b) placing a certain number of living cells1008 in a medium which covers the optical LID biosensor 1004 such thatthe living cells 1008 attach onto the surface 1010 of the biosensor 1004(step 2004); (c) applying a solution containing an agonist which has aknown affinity at a certain concentration into the cell medium for ashort time such that the translocation does not happen (step 2006); (d)after this short time, applying a solution containing a compound havinga certain concentration into the cell medium (step 2008); and (e)interrogating the optical LID biosensor 1004 and monitoring the timedependent optical response 1601 of the living cells 1008 cultured on theoptical LID biosensor 1004. It should be appreciated that like method1900, this method 2000 requires pre-knowledge about the target GPCR 1020in the living cells 1008 and also requires the pre-selection of anantagonist or angonist for pre-treating the living cell 1008 againstthis particular GPCR 1020.

It should be appreciated that the step 2006 and the step 2008 can becombined into one step; that is, the agonist known to the target GPCR inthe cell can be added into together with a compound. It also should beappreciated that similar to the method 1700, the compound to be testedcan be introduced first, followed by the addition of the known ofagonist.

Each of the methods 1700, 1900 and 2000 can be further enhanced by usinga self-referencing optical LID biosensor 1004. It is well known that theperformance of the optical LID biosensor 1004 is generally affected bythe designs and characteristics of the sensor, the optics, and by theenvironmental fluctuations including ambient temperature and pressure. Amain advantage of using the self-referencing optical LID biosensor 1004is that the top surface 1010 has both a reference region and a sampleregion which enables one to use the sample region to detect the massredistribution in the living cells 1008 and at the same time use thereference region which does not have living cells 1008 attached theretoto reference out spurious changes that can adversely affect thedetection of the mass redistribution within the living cells 1008.

In one embodiment, the self-referencing optical LID biosensor 1004 canbe made in accordance with method 2100 shown in FIG. 21. Thisself-referencing optical LID biosensor 1004 can be created by using thefollowing steps: (a) providing the optical LID biosensor 1004 (step2102); (b) physically blocking one region (reference region) of thesurface 1010 of the optical LID biosensor 1004 by using a soft stamp(e.g., rubber stamp) (step 2104); (c) placing a certain number of livingcells in a growth medium which covers an unblocked region (sampleregion) of the optical LID biosensor 1004 (step 2106); and (d) removingthe soft stamp after the living cells 1008 have attached to theunblocked region on the optical LID biosensor 1004 (step 2108). At thispoint, the living cell-based assay can be performed as described inmethods 1800, 1900 and 2000. It should be appreciated that differentmethods can also be applied to create the self-referencing LID sensorsfor cell studies. For example, a physical barrier can be used to dividethe sensor into two portions, and cells in a medium are only applied tocover one portion. After cell adhesion, the physical barrier can beremoved.

Referring now to another feature of the disclosed methods, it is wellknown that multiplexed cell assays have become increasingly important,not only for increasing throughput, but also for the rich andconfirmative information available from a single assay. As such, it isdesirable for the present methods to be performed in a multiplexingfashion, performing multiple assays at a single time.

In one embodiment, the present methods can be enhanced to performmultiple living cell-based assays at the same time by using the method2200 shown in FIG. 22. In accordance with method 2200 one can monitormass redistribution due to agonist-induced GPCR activation withinmultiple types of the living cells 1008 by: (a) providing an optical LIDbiosensor 1004 (step 2202); (b) blocking a portion of the top surface1010 of the optical LID biosensor 1004 by using a stamp that preventsthe attachment of the living cells 1008 to that portion of the opticalLID biosensor 1004 (step 2204); (c) placing a first type of living cells1008 in a cell medium which covers the unblocked portion of the surface1010 of the optical LID biosensor 1004 so the living cells 1008 are ableto attach to the unblock portion of the surface 1010 of the optical LIDbiosensor 1004 (step 2206); (d) removing the stamp from the top surface1010 of the optical LID biosensor 1004 (step 2208); (e) placing a secondtype of living cells 1008 in a cell medium which covers the optical LIDbiosensor 1004 so the second type of living cells 1008 are able toattach to the recently uncovered top surface 1010 of the optical LIDbiosensor 1004 (step 2210); (f) applying a solution containing acompound into the cell medium located on the top surface 1010 of theoptical LID biosensor 1004 (step 2212); and (g) interrogating theoptical LID biosensor 1004 to monitor time dependent optical responses1601 which indicate mass redistributions within the two types of livingcells 1008 on the optical LID biosensors 1004 (step 2214).

It should be appreciated that the two types of cells can be related;e.g., Chinese Hamster Ovary (CHO) cells versus engineered CHO cellscontaining an overexpressed target receptor. This approach not onlyenables multiplexed cell assays, but also provide confirmative resultsregarding to the compound effect on the target receptor by comparison ofthe optical responses of the same compound acting on two differentcells, since two cells are identical except for the target receptorexpression level.

In another embodiment, the present methods can be enhanced to performmultiple living cell-based assays at the same time using the method 2300shown in FIG. 23. In accordance with method 2300 one can monitor themass redistribution due to agonist-induced GPCR activation in multipletypes of living cells 1008 by: (a) providing a chamber (microplate)containing an array of the optical LID biosensors 1004 (step 2302); (b)placing a first type of living cells 1008 in a cell medium which coversone or more of the optical LID biosensors 1004 so the first type ofliving cells 1008 are able to attach to the surfaces 1010 of the one ormore optical LID biosensors 1004 (step 2304); (c) placing a second typeof living cells 1008 in a cell medium which covers one or more of theremaining uncovered optical LID biosensors so the second type of livingcells 1008 are able to attach to the surfaces 1010 of the one or moreremaining uncovered optical LID biosensors 104 (step 2306); (d) applyinga solution containing a compound into the cell mediums located on thetop surfaces 1010 of covered optical LID biosensors 1004 (step 2310);and (e) interrogating the covered optical LID biosensors 1010 to monitorthe time dependent optical responses 1601 which indicate massredistributions within the living cells 1008 on each of the coveredoptical LID biosensors 1004 (step 2312).

It should be appreciated that arrays of different DNA vectors containingdistinct target receptor genes in combination with transfection reagentscan be deposited onto a LID sensor; a single type of cell is placed andoverlaid with such array and uptakes the genes. Thus only cells overlaidon each spot area become transfected and therefore form a transfectedcell cluster array (U.S. Pat. No. 6,544,790 B1 “Reverse transfectionmethod”). Similarly, an array of functional receptor proteins can becomplexed with protein delivery reagents and can be used in a similartransfected cell cluster array (US2004/0023391A1 “Methods and devicesfor protein delivery”). Both types of transfected cell arrays can beused for compound screening using the current technology.

In yet another embodiment, the present methods can be further enhancedto perform multiple target screens in a single type of cells at the sametime by using method 2400 shown in FIG. 24. In accordance with method2400 one can screen agonists against multiple GPCRs 1020 within a singletype of living cells 1008 by performing the following steps: (a)providing a optical LID biosensor 1004 (step 2402); (b) placing theliving cells 1008 in a cell medium which covers the optical LIDbiosensor 1004 so the living cells 1008 are able to attach to thesurface 1010 of the optical LID biosensor 1004 (step 2404); (c) applyinga solution containing a cocktail solution of antagonists (step 2406);(d) applying a solution containing a compound into the cell mediumlocated on the top surface 1010 of the optical LID biosensor 1004 (step2408); and (e) interrogating the optical LID biosensor 1004 to monitor atime dependent optical response 1601 which indicates massredistributions within the living cells 1008 (step 24).

It should be appreciated that similar methods can be used to screenantagonist against multiple receptors in the same cell line by modifyingthe method 2400. Instead of a cocktail solution of antagonists in thestep 2406, one can use a solution of compounds of interest; at the sametime, a cocktail solution of agonists is used to replace the compoundsolution in the step 2408.

(1) Importance of Trafficking Kinetics Studies

Kinetics relating to cell signaling pathways and their associated cellactivity and other cellular changes are extremely important for not onlyunderstanding cell biology and physiology, but they are also importantfor cell assay development and drug discovery. For example, the EGFRsignaling network contains reactions ranging from almost instantaneousreactions (receptor phosphorylation after ligand binding) to reactionsthat occur over many minutes (vesicle formation or the sorting tolysosomes) or morphological changes in certain cell lines. Traffickingof the EGFR is regulated at multiple steps, including endocytosis, earlyendosomal sorting, and lysosome targeting. After internalization, theEGFR are either shuttled back to the plasma membrane or transported intolate or multivesicular endosomes. The receptors in the late endosomesare further sorted to lysosomes for degradation or recycled back to thecell surface. The occupancy of the receptors dictates their ability toparticipate in each step of the sorting process. Although the principalhierarchy of the EGFR signaling cascade and its activation sequences iswell known, the complicated kinetics network and critical signalingevents that control such divergent cellular responses as cell growth,survival, or differentiation are poorly understood. Technologies thatcan measure the real time kinetics of cellular responses throughligand-mediated EGFR activation would greatly benefit understandingabout the dynamics of signaling cascades and networks.

(2) G-Protein Coupled Receptor Pathways

GPCRs belong to a family of cell surface receptors, and are among themost common targets that new drug compounds are designed against. SinceGPCRs can transduce exogenous signals (i.e., the presence of stimulisuch as a new drug) into intracellular response(s) makes them extremelyvaluable as drug targets and for the testing of new drugs.

GPCRs participate in a wide array of cell signaling pathways. Ligandbinding initiates a series of intracellular and cellular signalingevents, including receptor conformational changes, receptoroligomerization, G protein activation (GDP-GTP exchanges on G_(α)subunit, G_(α) and G_(βγ) disassociation, G protein decoupling from thereceptor, generation of G_(α)- and G_(βγ)-signaling complexes), anddownstream signaling activation that leads to second messengergeneration (Ca²⁺ mobilization, inositoltriphosphate generation, and/orintracellular cAMP level modulation) and ultimately results in changesof specific gene expression. Ligand-mediated GPCR activation also leadsto the desensitization of GPCRs from the cell surface and trafficking ofmany intracellular proteins, as well as changes in phenotypes,morphology and physical properties of the target cells. These changescould be static, long-lasting or dynamic (e.g., cycling or oscillation).Distinct signaling events exhibit significantly different kineticsranging from milliseconds (e.g., GPCR conformational changes) to tens ofseconds (e.g., Ca²⁺ flux) to even tens of minutes (e.g., geneexpression, or morphological changes). Current GPCR assays includeligand-receptor binding, second messenger (Ca²⁺, cAMP of IP3) assays,protein interaction assays, translocation assays and reporter geneassays. Since GPCR activation ultimately leads to protein traffickingand/or morphological changes, methods that can study the action of anycompounds through the GPCRs on cell surface and the consequent events(e.g., trafficking and/or morphological changes) of the effected cellswould be desired.

(3) Receptor Tyrosine Kinase (RTK) Signaling Pathways

(a) Diversity of RTKs

A large group of genes in all eukaryotes encode for proteins thatfunction as membrane spanning cell surface receptors. Membrane receptorscan be classified into distinct families based upon the ligands theyrecognize, the biological responses they induce, and the primarystructures they have. One large family of cell surface receptors isendowed with intrinsic protein tyrosine kinase activity. These receptortyrosine kinases (RTKs) catalyze transfer of the phosphate of ATP tohydroxyl groups of tyrosines on target proteins. RTKs play an importantrole in the control of most fundamental cellular processes including thecell cycle, cell migration, cell metabolism and survival, as well ascell proliferation and differentiation.

Receptor tyrosine kinases (RTKs) belong to a super family of proteintyrosine kinases (PTKs). PTKs are a large and diverse multigene family.Their principal functions involve the regulation of multicellularaspects of the organism. Cell to cell signals concerning growth,differentiation, adhesion, motility, and death, are frequentlytransmitted through tyrosine kinases. In contrast, many of theserine/threonine kinase families, such as cyclin dependent kinases andMAP kinases, are conserved throughout eukaryotes and regulate processesin both unicellular and multicellular organisms. In humans, tyrosinekinases have been demonstrated to play significant roles in thedevelopment of many disease states, including diabetes and cancer.Historically, tyrosine kinases define the prototypical class ofoncogenes, involved in most forms of human malignancies. Tyrosine kinasegenes have also been linked to a wide variety of congenital syndromes.Tyrosine kinases contain highly conserved catalytic domains similar tothose in protein serine/threonine and dual-specificity kinases but withunique subdomain motifs clearly identifying members as tyrosine kinases.Tyrosine kinase genes have been characterized in poriferans, cnidarians,nematodes, annelids, arthropods, echinoderms, and chordates, and others.The human tyrosine kinases may be grouped into 20 receptor and 10non-receptor classes, based on either intron/exon structure orphylogenetic sequence analysis.

All receptor tyrosine kinases contain an extracellular ligand bindingdomain that is usually glycosylated, and involved in receptordimerization. The ligand binding domain is connected to the cytoplasmictyrosine kinase domain by a single transmembrane helix. The cytoplasmicdomain contains a conserved protein tyrosine kinase (PTK) core andadditional regulatory sequences that are subjected toautophosphorylation and phosphorylation by heterologous protein kinases.RTKs can be further classified into several sub-families of receptors:insulin receptor (IR) family, epidermal growth factor (EGF) receptorfamily, PDGF receptor family, for example. The epidermal growth factor(EGF) family of receptor tyrosine kinases consists of four receptors,EGF-R (ErbB1), ErbB2 (Neu), ErbB3, and ErbB4.

(b) Dimerization of RTKs

With the exception of the insulin receptor (IR) family of RTKs, allknown RTKs (e.g., epidermal growth factor (EGF) receptor, PDGF receptor)are monomers in the cell membrane. Ligand binding induces dimerizationof these receptors resulting in autophosphorylation of their cytoplasmicdomains. Members of the IR family are disulfide linked dimers of twopolypeptide chains forming a 22 heterodimer. Insulin binding to theextracellular domain of the IR induces a rearrangement in the quaternaryheterotetrameric structure that leads to increased autophosphorylationof the cytoplasmic domain.

Although all RTKs are activated by dimerization, different ligandsinduce the formation of different active dimeric states. Specificligands define the dimer pair; the dimer pair, in turn, defines thesignaling pathway. Structural studies of growth hormone (GH) in complexwith GH receptor (GHR) and erythropoietin (EPO) in complex with EPOreceptor (EPOR) show that these cytokines are bivalent, and one ligandbinds simultaneously to two receptor molecules to form a 1:2(ligand:receptor) complex. Receptor dimerization is further stabilizedby additional receptor:receptor interactions. Only certain forms ofreceptor dimers with unique configurations of the extracellular andcytoplasmic domains of both RTKs and cytokine receptors lead totrans-autophosphorylation and PTK stimulation.

(c) EGFR

The EGR receptors, consisting of four members as mentioned above, belongto the tyrosine kinase family of receptors and are expressed invirtually all organs of mammals. EGF receptors play a complex roleduring embryonic and postnatal development and in the progression oftumors. Apart from their roles in growth and differentiation, EGFRreceptors participate in transactivation processes and are involved incrosstalk with other receptors such as GPCRs.

(d) EGFR Signaling Pathways

The engagement of EGFR by its cognate ligand results in the generationof a number of intracellular signals (as shown in FIG. 38). Followingligand binding, the initial changes are receptor dimerization to formhomo-dimers or hetero-dimers with other family members, activation ofthe kinase activity of the receptor, and autophosphorylation of thereceptor on tyrosine residues of the cytoplasmic domain. Receptorautophosphorylation results in the creation of docking sites for anumber of secondary signaling proteins bearing specific proteininteraction domains such as the Src homology 2 (SH2) domain, whichinteract specifically with phosphorylated tyrosine residues. Eachdimeric receptor complex will initiate a distinct signaling pathway byrecruiting different SH2-containing effector proteins. As a consequenceof this interaction, these secondary signaling proteins themselves maybecome activated and trigger a number of downstream signals. Forexample, the activated EGF-R dimer complexes with the adapter protein,Grb, coupled to the guanine nucleotide releasing factor, SOS. TheGrb-SOS complex can either bind directly to phosphotyrosine sites in thereceptor or indirectly through Shc. These protein interactions bring SOSin close proximity to Ras, allowing for Ras activation. Thissubsequently activates the ERK and JNK signaling pathways that, in turn,activate transcription factors, such as c-fos, AP-1, and Elk-1, thatpromote gene expression and contribute to cell proliferation. Oneparticular pathway that promotes cell proliferation involves thesignaling proteins Shc, Grb2, Sos, Ras, Raf, MEK, ERK and ERK/MAPK, andis known as Ras/MAPK pathway.

(i) EGFR Signaling and Mass Redistribution

Ligands for EGFRs include EGF, TGF-α, amphiregulin, heparin-bindingEGF-like growth factor, betacellulin, and epiregulin. The EGFR can beactivated by the binding of any one of a number of different ligands,each of which appears to stimulate a somewhat different spectrum ofbiological responses. Furthermore, different EGFR ligands vary in theirability to bind to the receptor as a function of receptormicroenvironment, such as intravesicular pH.

After binding, the activated EGFR is rapidly internalized byendocytosis. Receptor-mediated endocytosis allows the specific removalof cell surface receptors and their cargo from the plasma membrane andtargets them to endosomes, where they are sorted for downregulation orrecycling. After endocytosis, receptor-ligand complexes pass throughseveral different compartments that vary in their intravesicular milieu.Receptor movement among cellular compartments (referred as trafficking)has a significant effect on the activity of the complexes. The differentintracellular compartments also vary in their access to some of thesubstrates of the EGFR kinase. The conjoined relationship betweensubstrate access and ligand-dependent activity in different endocyticcompartments suggests that trafficking could function to “decode” theinformation unique to each ligand. Furthermore, the persistence ofligand-receptor interactions controls receptor trafficking. Thus,receptor endocytosis and degradation is an important mechanism forcontrolling the magnitude of the signal, the specificity of theresponse, and the duration of the response.

Ligand-induced internalization of the EGFR is a saturable process andincreases in the level of EGFR expression beyond a certain thresholdlead to impaired internalization of the receptor.

EGF receptors can be internalized by either an induced pathway or aconstitutive pathway. The vesicles formed through the induced pathwayare referred to as coated-pit mediated early endosome (EE) vesicles. AllEE vesicles go through a sorting stage and can either return to the cellsurface or merge into the late endosomes (LE). When an EE vesiclerecycles back to the plasma membrane (PM), all of its receptors becomepart of the PM and any unbound ligand is released into the extracellularmedium. Similarly, when an EE vesicle merges into the LE, all of itscontents are transferred to the LE. The rates of recycling to the plasmamembrane and of merging into the late endosome can depend on the type ofEE vesicle. Endocytic vesicles are recycled back to the plasma membraneeither at a very fast rate or after a time lag (i.e., slowly).Generally, the coated-pit EE vesicles recycle back to the plasmamembrane slowly and, as a result, a considerable percentage of thecoated-pit EE vesicles merge into the LE. In contrast, constitutive EEvesicles have a faster recycle rate and thus most of them return to theplasma membrane. The receptors go through a second stage of sorting inthe LE and either are tagged for degradation and sent to the lysosome orare recycled back to the cell surface. A small vesicle breaks away fromthe sorting endosome at a certain rate. This vesicle either fuses to thelysosome for its contents to be degraded or it recycles back toward theplasma membrane. Mechanistically, receptors recycling from the lateendosomes are likely to pass through the golgi. The net outcome of thoseendocytic processes leads to a directional mass re-distribution in cellsafter EGFR activation.

Depending on the cellular context of a specific cell line,ligand-induced EGFR activation could lead to distinct signaling pathwaysor multiple signaling pathways in which one becomes dominant compared toothers. Furthermore, the expression level of EGFRs could vary from oneto another cell line. Because of that, the mass redistribution withinthe cells mediated by ligand-induced EGFR activation could vary amongdifferent cell lines. For example, the human epidermoid carcinoma A431cell is known to endogenously over-express EGFRs (˜1,700,000 copies percell), and thus has been used as an ideal model for EGFR signaling (D.W. Barnes, “Epidermal growth factor inhibits growth of A431 humanepidermoid carcinoma in serum-free cell culture,” J. Cell. Biol. 1982,93, 1-4). Upon the binding of EGF, EGFRs in the A431 cells becomeactivated, and lead to various cellular responses through distinctpathways including the Ras/MAPK pathway. For example, stimulation ofquiescent A431 cells with EGF at 37° C. ultimately leads to receptorendocytosis, refractile morphological changes and cell detachment fromthe extracellular matrices (Z. Lu, G. Jiang, P. Blume-Jensen, and T.Hunter, “Epidermal growth factor-induced tumor cell invasion andmetastasis initiated by dephosphorylation and downregulation of focaladhesion kinase,” Mol. Cell. Biol. 2001, 21, 4016-4031. and Y. Danjo andI. K. Gipson, “Actin ‘purse string’ filaments are anchored byE-cadherin-mediated adherens junctions at the leading edge of theepithelial wound, providing coordinated cell movement,” J. Cell Sci.1998, 111, 3323-3332). Again, receptor endocytosis is an importantcellular process to attenuate the EGF signal, although some evidencesuggests that EGF receptor complexes continue to signal in endosomalcompartments. The endocytosis process involves multiple steps:recruitment of intracellular components to the activated receptors,subsequent internalization of the resulted complexes into endosomes,movement of the internalized receptor complexes among severalintracellular compartments, and ultimately degradation and recyclingback to the cell membrane. In addition, because of the size of thoseligands, the density of cell surface receptors, and density andmorphology of cell lines used (such as the A431 cell line) as well asthe receptor trafficking after activation, there are a number ofsignaling events in RTK pathways that give rise to directional massredistribution. For example, the binding of ligands to cell surfaceEGFRs leads to an increase of mass at the cell surface; the sequentialautophosphorylation and intracellular components interacting with theactivated EGFRs results in a net zero-change of mass redistribution fora short period of time. The trafficking of activated receptors leads tosignificant mass redistribution within different compartments of eachcell.

Another possible resource for mass redistribution is due to cytoskeletonrearrangement. For example, the EGFR trafficking process is initiated byrecruitment of the receptor into a clathrin-coated pit at the plasmamembrane, a structure formed by assembly of clathrin and adaptors into aprotein lattice on the membrane's cytosolic face. Polymerization ofclathrin into a hexagonal array provides a scaffold for organizing theadaptors, which recognize sequence motifs in the cytoplasmic domains ofinternalized receptors. The actin cytoskeleton is believed to contributeto the formation of clathrin-coated pits, although the specificcomponents that connect actin filaments with the endocytic machinery areunclear. Cortactin is an F-actin-associated protein, localizes withinmembrane ruffles in cultured cells, and is a direct binding partner ofthe large GTPase dynamin. Cortactin, together with actin and dynamin,are important components of the receptor-mediated endocytic machinery(Bajzer, Z., et al., “Binding internalization, and intracellularprocessing of proteins interacting with recycling receptors—a kineticanalysis”, J. Biol. Chem. 1989, 264:13623-13631).

(ii) Constitutive Activity of EGFRs

It is thought that receptor monomers are in equilibrium with receptordimers. A limited population of receptor dimers exist with quaternarystructures of their extracellular and cytoplasmic domains inconfigurations that are compatible with trans-autophosphorylation andstimulation of PTK activity (active dimer). Ligand binding to theextracellular domain stabilizes the formation of active dimers andconsequently PTK stimulation. It has been proposed that active dimersexist even in the absence of ligand binding since autophosphorylation ofRTKs can be enhanced by inhibitors of protein tyrosine phosphatases orby receptor overexpression even in the absence of ligand binding.Experiments show that 2% of the unbound (ligand free) and 15% of theligand-bound receptors on the plasma membrane get internalized per min.Furthermore, in quiescent A431 cells, obtained by culturing the cells ina medium containing relatively low concentrations of growth factors suchas fetal bovine serum (FBS) (less than 0.5% in weight) or without anyFBS, there is still some degree phosphorylation of the EGFR due to itsconstitutivity.

FIG. 7 shows that EGF stimulation lead to a strong dose-dependentdynamic response (See FIG. 7A); three major biosensor parametersdefining the response are significantly changed as the concentration ofEGF increases. The higher the EGF concentration goes, 1) the greater theamplitudes of both P-DMR and N-DMR signals, 2) the faster the kineticsof both P-DMR and N-DMR events is, and the 3) shorter the time resultingin the transition from the P-DMR to N-DMR event (the transition time τ).When the amplitudes of the P-DMR events showed a complicate relationshipwith the EGF concentrations, the amplitudes of the N-DMR signals showeda strong and saturable dose dependence on EGF, resulting in an EC₅₀ of˜1.45 nM (see FIG. 7 b). The transition time τ in seconds was found todecrease exponentially with the increasing concentration of EGF (seeFIG. 7 c): In addition, the decay of the N-DMR signal can be fitted withnon-linear regression. The one-phase decay constant κ obtained also gaverise to a typical saturable response with a Kd of 5.76 nM (see FIG. 7d). Those dose-dependent kinetics parameters (the transition time andthe decay constant of the N-DMR phase) were in excellent agreement withthe previous experimental data and computational predictions relating tokinetics of expression of the target gene, C-fos, in HeLa cells and ofEGFR endocytosis (Schoeberl, B., C. Eichler-Jonsson, E. D. Gilles, andG. Muller. “Computational modeling of the dynamics of the MAP kinasecascade activated by surface and internalized EGF receptors”. Nat.Biotech. 2000, 20:370-375). These results indicated that EGF-inducedcell morphological changes and receptor endocytosis are DMR events andthe DMR is an EGFR activation dependent event.

(e) PDGFR

Similar to EGFRs, platelet-derived growth factor (PDGF) has been shownto drive cellular responses including proliferation, survival,migration, and the deposition of extracellular matrix (ECM) and tissueremodeling factors. Knockout studies have demonstrated that many ofthese cellular responses to PDGFs are essential during mousedevelopment. There are two ligands, PDGFa and PDGFb, and two receptors,PDGF receptor alpha and PDGF receptor beta (PDGFRα and PDGFRβ,respectively). PDGFb and PDGFRβ are essential for the development ofsupport cells in the vasculature, whereas PDGFa and PDGFRα are morebroadly required during embryogenesis, with essential roles in numerouscontexts, including central nervous system, neural crest and organdevelopment.

The PDGF signaling network consists of four ligands, PDGFA-D, and tworeceptors, PDGFRα and PDGFRβ. All PDGFs function as secreted,disulfide-linked homodimers, but only PDGFA and B can form functionalheterodimers. PDGFRs also function as homo- and heterodimers, and invitro assays have demonstrated that the ligands differ in theiraffinities for the, αβ and ββ receptors. All known PDGFs havecharacteristic ‘PDGF domains’, which include eight conserved cysteinesthat are involved in inter- and intramolecular bonds.

PDGFRs are receptor tyrosine kinases, just like EGFRs. Each receptor hasfive immunoglobulin repeats in the extracellular ligand-binding domainand a split tyrosine kinase domain in the cytoplasmic region. Uponligand binding, PDGFRs dimerize, activating the tyrosine kinase domains,which then autophosphorylate several tyrosine residues in the receptorcytoplasmic domains. This creates docking sites for signaling proteinsand adaptors that initiate signal transduction upon PDGFR binding. Bothreceptors can activate many of the same major signal transductionpathways, including the Ras-MAPK (mitogen activated protein kinase),phosphatidylinositol 3-kinase (PI3K) and phospholipase C pathways.However, the array of interacting proteins differs slightly betweenPDGFRα and PDGFRβ, resulting in some differences in their functionalcapabilities in vivo.

Similar to EGFR signaling, the activation of PDGFRs could also lead tosignificant mass redistribution which can be monitored and analyzed byoptical biosensors.

(f) Other RTKs

Tyrosine kinases are primarily classified as receptor tyrosine kinase(RTK) e.g. EGFR, PDGFR, FGFR and the IR, and non-receptor tyrosinekinase (NRTK) e.g. SRC, ABL, FAK and Janus kinase. Besides EGFRs andPDGFRs, others receptor tyrosine kinases include insulin receptors,insulin-like growth factor I receptors (IFG-1R), nerve growth factorreceptors (NGFRs), fibroblast growth factor receptors (FGFRs).Similarly, these RTKs are not only cell surface transmembrane receptors,but are also enzymes having kinase activity. The structural organizationof the receptor tyrosine kinase exhibits a multidomain extracellularligand for conveying ligand specificity, a single pass transmembranehydrophobic helix and a cytoplasmic portion containing a tyrosine kinasedomain. The kinase domain has regulatory sequence both on the N and Cterminal end.

The NRTK are cytoplasmic proteins, exhibiting considerable structuralvariability. The NRTK have a kinase domain and often possess severaladditional signaling or protein-protein interacting domains such as SH2,SH3 and the PH domain. The tyrosine kinase domain spans approximately300 residues and consists of an N terminal lobe comprising of a 5stranded β sheet and one α helix, while the C terminal domain is a largecytoplasmic domain that is mainly α helical. ATP binds in the cleft inbetween the two lobes and the tyrosine containing sequence of theprotein substrate interacts with the residues of the C terminal lobe.RTKs are activated by ligand binding to the extracellular domainfollowed by dimerization of receptors, facilitatingtrans-phosphorylation in the cytoplasmic domain whereas the activationmechanism of NRTK is more complex, involving heterologousprotein-protein interaction to enable transphosphorylation.

(4) Cytoskeleton Modulation

Cytoskeleton is a unique and cellular “scaffolding” or “skeleton”contained within the cytoplasm. Cytoskeleton is a complex and dynamicnetwork of protein filaments that extends throughout the cytoplasm ofeukaryotic cells. Cytoskeleton is involved in executing diverseactivities in cells. It maintains cell shape by providing tensilestrength for the cells. It also enables some cell motion (usingstructures such as flagella and cilia), and plays important roles inboth intra-cellular transport (the movement of vesicles and organelles,for example) and cellular division. The cytoskeleton is involved inintracellular signaling and trafficking by providing the “track” onwhich cells can move organelles, chromosomes and other things.

Eukaryotic cells are given shape and organized by the cytoskeleton. Thelong fibers of the cytoskeleton are polymers of subunits. The primarytypes of fibers comprising the cytoskeleton are microfilaments,microtubules, and intermediate filaments. (i) Microfilaments are twisteddouble strands consisting of a string of proteins, typically from 7 nmto 12 cm long. The protein is actin. Its function helps musclecontraction, cell shape, and movement in cytoplasm. (ii) Intermediatefilaments are made of eight subunits in rope-strands. The proteinsstructure varies with different tissue types. This component helpsmaintain shape, support nerve cell extensions, and attach cellstogether. (iii) Microtubules are tubes made up of spiraling, two-partsubunits. It is made of tubulin. It aids in chromosome movement,movement of organelles, and the movement of cilia and flagella. Forexample, in epithelial cells of the intestine, all three types of fibersare present. Microfilaments project into the villi, giving shape to thecell surface. Microtubules grow out of the centrosome to the cellpheriphery. Intermediate filaments connect adjacent cells throughdesmosomes.

(a) Cytoskeleton Structure

The cytoskeleton is a cellular “scaffolding” or “skeleton” contained, asall other organelles, within the cytoplasm. It is a dynamic structurethat maintains cell shape, enables some cell motion (using structuressuch as flagella and cilia), and plays important roles in bothintra-cellular transport (the movement of vesicles and organelles, forexample) and cellular division. Eukaryotic cells contain three kinds ofcytoskeletal filaments: actin filaments, intermediate filaments andmicrotubules (Janmey, P. A. (1998). The cytoskeleton and cell signaling:component localization and mechanical coupling. Physiol. Rev. 78,763-781)) Actin filaments that are around 7 nm in diameter. Thisfilament is composed of two actin chains oriented in a helicoidal shape.They are mostly concentrated just beneath the plasma membrane, as theykeep cellular shape, form cytoplasmatic protuberancies (like pseudopodsand microvillus), participate in some cell-to-cell or cell-to-matrixjunctions and the transduction of signals. They are also important forcytokinesis and, along with myosin, muscular contraction. Intermediatefilaments that are around 8 to 11 nanometers in diameter. They are themore stable (strongly bound) and heterogeneous constituents of thecytoskeleton. They organize the internal 3-dimensional structure of thecell (e.g., they are structural components of the nuclear envelope orthe sarcomeres). They also participate in some cell-cell and cell-matrixjunctions. Microtubules that are hollow cylinders of about 25 nm.,formed by 13 protofilaments which, in turn, are polymers of alpha andbeta tubulin. They have a very dynamic behavior, binding GTP forpolymerization. They are organized by the centrosome. These filamentsplay key roles in intracellular transport (associated with dyneins andkinesins, they transport organelles like mitochondria or vesicles), andthe mitotic spindle.

(b) Controlled Releasing of Biomaterials from Permeabilized Cells

Discussion regarding the controlled release of biomaterials frompermeabilized cells can be found in Negrutskii, B. S. and Deutscher, M.P. (1992) “A sequester pool of aminoacyl-tRNA in mammalian cells” Proc.Natl. Acad. Sci. USA 89, 3601-3604; Negrutskii, B. S., Stapulionis, R.and Deutscher, M. P. (1994) “Supramolecular organization of themammalian translation system” Proc. Natl. Acad. Sci. USA 89, 3601-3604which are herein incorporated in their entireties by reference and atleast for material related to controlled release of biomaterials frompermeabilized cells.

A living cell is a macromolecular assembly. Many studies have shown thatendogenous macromolecules are highly organized within the cytoplasm ofmammalian cells through direct binding to cytoskeletal elements. Thecytoskeleton, particularly the actin microfilament network, plays animportant role in maintaining this organization.

Permeabilized cells have been used to examine cell architecture.Treatment of the cells with many chemicals or biologicals can result inthe pore formation in cell surface membrane which leads to permeabilizedcells. These chemicals or biologicals include detergents such as saponinand filipin, or toxin such as digitonin or streptolysin O. Compared toother pore-forming reagents, however, saponin has the advantage whencarefully titrated of causing minimal damage to internal membranes andleading to a very uniform population (>97%) of permeabilized cells.Saponin, a plant-derived glycoside, is well known for its ability torender the plasma membrane sufficiently porous to permit solubleproteins to diffuse away. Although the saponin-treated cells undergo theloss of some portions of biomacromolecules, the permeabilized cellsresulted still retain the most of biological functions of living cells.This has been evidenced by the fact that protein synthesis in thesepermeabilized cells remains at a high level, despite the complexity ofthe process, which suggesting that this system has retained much of theoriginal structural integrity of intact cells. This is because mostmacromolecules are sequestered as part of an organized cell structure,therefore being not released from these permeabilized cells. Forexample, components of the translation apparatus such as tRNA,aminoacyl-tRNA synthetases, and EFl are normally tightly sequestered inpermeabilized cells. Not only protein synthesis machinery is sequesteredby the cytoskeleton, many other components of the cell are also stablyor transiently associated with cellular structure; these transientlyassociated components can be partially released from permeabilizedcells.

However, upon disruption of microfilaments there is a dramatic reductionof protein synthesis accompanied by release of these translationcomponents from the cells. Also, many other sequesteredbiomacromolecules are released from these permeabilized cells afterdisrupting the cytoskeleton structure. These further released materialsfrom the permeabilized cells result in a loss in mass; thus resulting inthe changes in effective refractive index of the cell layer on thesurface of an LID sensor which can be detected by LID sensors. Thus, thechanges obtained using optical biosensors can be used as an indicator ofmodulators that interfere with the cytoskeleton structure.

Traditionally, methods to screen modulators that interfere with thecytoskeleton structure are mainly based on binding affinity measurementsusing in vitro assays, including actin binding protein assays,microtubule stabilization/destabilization assays, and actin/tubulinpolymerization assay. Other methods are based on high resolutionfluorescence imaging technique to directly visualize the intracellularcytoskeleton structure, or to measure the motility of cells aftercompound treatments, or to measure the activation ofcytoskeleton-interacting maker proteins such as Cdc42 or Rho.

Disclosed herein are label-free detection methods using opticalbiosensors to screen modulators that interfere with cytoskeletonarrangement.

Disclosed are methods in the optical biosensor field and, in certainembodiments, to a system and method for using an optical labelindependent detection (LID) biosensor (e.g., waveguide grating-basedbiosensor) to monitor in real time compound-induced releasing ofintracellular components that are sequestered by the cytoskeleton inpermeabilized and functional cells. Disclosed are methods usingchemicals or biologicals to generate permeabilized cells which permitsoluble proteins to diffuse away. Disclosed are systems and methods forusing a LID biosensor to screen modulators of cytoskeleton componentsusing optical biosensors.

Unlike all the existing assay technologies for cytoskeleton arrangement,the disclosed methods provide a label-free and real time method toscreen modulators that interfere with the cytoskeleton structure. Inaddition, unlike all the existing and cell-based assays for cytoskeletonarrangement, the present methods take advantage of permeabilized cellsthat retain most of the biological functions of living cells, but withsignificantly more simplicity than living cells. Unlike the fluorescenceimaging-based assays that normally screen modulators against a singletarget, the present methods offer multiplexing capabilities, i.e. thecapability to screen modulators that interfere with multiple targetswithin cells. Combined with a total internal reflection fluorescenceimaging technique, the disclosed methods provide high informationcontent screening, including kinetics, affinity, target(s) that areinvolved, as well as toxicity.

FIG. 25 shows an example of a method based on the measurement in realtime of compound-induced releasing of intracellular components that aresequestered by the cytoskeleton in permeabilized and functional cells.The method involves the use of pore-forming reagents (e.g, saponin) togenerate permeabilized cells which permit soluble proteins to diffuseaway. It is known that treatment of the cells with many pore-formingreagents leads to permeabilized cells. Since intracellularmacromolecules are highly organized within the cytoplasm of mammaliancells through direct binding to cytoskeletal elements, the permeabilizedcells still retain most of the biological functions of living cells bysequestration of intracellular machinery through the cytoskeletonsuper-assembled structure, although the saponin-treated cells undergothe loss of some portions of biomacromolecules. However, upon disruptionof microfilaments there is a dramatic reduction of protein synthesisaccompanied by release of these translation components from the cells.Also, many other sequestered biomacromolecules are released from thesepermeabilized cells after disrupting the cytoskeleton structure. Thesefurther released materials from the permeabilized cells result in theloss in mass; thus resulting in the changes in effective refractiveindex of the cell layer on the surface of a LID biosensor which can bedetected by LID biosensors. Thus, the changes obtained using opticalbiosensors can be used as an indicator of modulators that interfere withthe cytoskeleton structure. In one embodiment, the present methods canbe used to screen modulators that interfere with the cytoskeletonstructure using the method 2500 shown in FIG. 25. In accordance withmethod 2500 one can monitor the mass redistribution due to poreformation of cell surface membranes induced by pore-forming reagentssuch as saponin in living cells 1008 by: (a) providing an optical LIDbiosensors 1004 (step 2502); (b) placing cells 1008 in a cell mediumonto the said sensor 1004 (step 2504); (c) Optionally applying a buffersolution (step 2506); (d) applying a solution containing a compound intothe cell mediums located on the top surfaces 1010 of covered optical LIDbiosensors 1004 (step 2508); applying a solution containing apore-forming reagent (step 2510); and (e) interrogating the coveredoptical LID biosensors 1010 to monitor the time dependent opticalresponses which indicate mass redistributions within the permeabilizedcells 1008 (step 2512). A Pore-forming reagent is a chemical orbiological compound or composition that can result in the formation ofpores in cell surface membranes when the cells are exposed to thereagent.

Typically, measurements or assays relating to cell function oractivities using optical biosensors, as disclosed herein, can be done inreal time. Although a variety of optical output parameters can be usedfor cell monitoring and examination, the output parameters relating tothe kinetics of stimulation-induced directional mass redistribution aretwo parameters for monitoring cell signaling and its consequences inreal time.

Cell signaling pathways, including but not limiting to Ras/MAPK pathway,cAMP pathway, GPCR signaling pathways, RhoA pathway, Akt pathway,intregin pathways, GPCR attenuation pathways, G protein pathways, Capathways, phospholipase C pathway, cell transformation pathway, cellmigration pathways, cell adhension pathways, etc, can be associated withthe DMR signals measured using optical biosensors. For example,activation of the MAPK kinase pathway has been identified as a mechanismthat integrins use to regulate gene expression leading to cell shapechanges during cell spreading or migration Epithelial cells respond toextracellular matrix (ECM) cause integrin-mediated FAK phosphorylationthat in turn phosphorylates the surrounding proteins (paxillin, Fyn/shc,and src) and leads to signal amplification. FAK also binds PI-3 kinaseand is upstream of the MAP kinase pathway. When MAPkinase or PI-3 kinasewas inhibited, actin reorganization was blocked. Src phosphorylatesp190RhoGAP, inactivating its GAP function that may allow RhoGTP to stayactive longer, promoting further signal amplification. Activated RhoGTPbinds to downstream kinases such as Rho-associated coiledcoil-containing protein kinase (p160ROCK) and p140 diaphanous (p140Dia)to increase actin polymerization and contraction. Actin reorganizationassists integrin clustering, allowing more ECM binding that increase FAKphosphorylation and other signal transduction events. Because cellsignaling pathways and their cellular consequences are stronglydependent on the cellular context, it should be understood that for agiven cell type, the activation of a given signaling pathway through aspecific and predetermined target may not lead to any DMR (meaning thata stimulation may only lead to a net-zero DMR phase), or in some cases,result in a distinct DMR response from that obtained using a differentcell line. Furthermore, the activation of a particular signaling pathwaymediated by a stimulus through distinct targets (e.g., a GPCR versus aRTK) might lead to identical or distinct DMR responses of a single typeof cells. In other words, the DMR mediated by a stimulus through aspecific target is an integrated and representative presentation of theinteraction of numerous cell-signaling networks. Furthermore, thestimulus-induced cellular responses might also depend on cell conditions(e.g., proliferating versus quiescent states, or differentiating ornon-differentiating, the state of cycles −G1 versus other states, etc.).In some cases, the cells attached on the sensor surface might have to bepre-treated in order to reach a desired state. For example, to study theactivation of certain specific signaling pathways that are activatedthrough stimulus-induced activation of certain targets and ultimatelylead to cell growth and proliferation and/or differentiation, cells arepreferably to be in a quiescent state. In order to reach quiescentstate, cells at the proliferating state have to be pre-treated with amedium that has very little or not any growth factors or the like thatstimulate cell growth and proliferation. A pre-treatment time is alsocritical to reach the desired state, because of the cellular functionand dynamics.

Disclosed are methods that are specifically used to study the activationof cell signaling pathway(s) and its consequences, which require thepre-treatment of the cells to reach the quiescent state rather than theproliferating state. RTKs can be an example of this. In one embodiment,disclosed are methods for monitoring ligand binding and sequentialsignaling event in cells in real time, which comprises: (a) providing anoptical-based label free biosensor; (b) placing cells having a receptortyrosine kinase on the sensor surface; the cells are suspended in amedium containing certain concentration of serum which is required forthe attachment and growth of the cells on the biosensor surface; (c)optionally starving the adherent cells in a medium containing no or lowconcentration of serum for certain time at 37° C.; (d) placing thebiosensors having a layer of the cells into the detection system andmonitoring the response; (e) optionally applying a buffer solution atleast once into the cell medium for a certain amount of time; (f)optionally applying a solution containing a ligand to the RTK into themedium; and (g) monitoring the time dependent response of the layer ofthe adherent cells. The starvation treatment of the cells having a RTKis preferable for maximizing the cells response to ligands, becausethere are multiple growth factors found in serum. These growth factorsinclude PDGF platelet-derived growth factor), EGF, insulin, TGF-α,insulin-like growth factor I (IGF-I), and nerve growth factor (NGF).Medium with no or low concentrations (˜0.5%) of serum or bovine serumalbumin (BSA) can be used for starving the cells. The starvation timecan typically involve an overnight starvation. It should be understoodthat such methods disclosed herein are not limited to RTK signalingstudies; and can be applied to many other types of targets such asmitogenic GPCRs and their ligands.

In another embodiment, disclosed are methods for measuring ordetermining the expression level and cell-surface expression level ofRTKs in cells, which comprises: (a) providing a microplate with multiplewells, each well having an optical-based label free biosensor embeddedin the bottom; (b) providing multiple types of cells; (c) placing onetype of cell suspended in a medium into at least one well; (d) culturingthe cells in an appropriate medium for attachment and growth until acertain level of confluence is reached; (e) placing the microplatehaving biosensors, each biosensor covered by a layer of the cells into adetection system and monitoring the response; (f) applying a solutioncontaining a ligand to the RTK into the medium; (g) monitoring andcomparing the time dependent response of the layer of different types ofcells. The different types of cells might require different growthmedium. For same type of cells, different growth mediums can be appliedfor studying the effect of the medium on the cell surface expressionlevel of the RTK of interest.

In another embodiment, disclosed are methods for determining the potencyof ligands to RTKs using optical biosensors, which comprises: (a)providing a microplate with multiple wells, each well having anoptical-based label free biosensor embedded in the bottom; (b) providinga certain number of cells having relatively high expression level of aRTK in a medium such that the cells become attached to each biosensorwith a desired confluence; (c) exchanging the medium to starve theadherent cells for certain time; (d) placing the microplate havingbiosensors, each biosensor covered by a layer of the cells into adetection system and monitoring the response; (f) applying a solutioncontaining a ligand at different concentrations into the medium coveringeach biosensor; (g) monitoring and comparing the dose- andtime-dependent response of the cells. The dose-dependent binding and DMRsignals as well as their corresponding kinetics can be used to determinethe potency of ligands to the RTK of interest. It should be understoodthat such methods can also be used for determining the potency of aninhibitor against a downstream target that plays a significant role inthe overall DMR signal due to the activation of the RTK or othersignaling molecule, and subsequent cellular changes. For example, theEGF-induced DMR signal of quiescent A431 cells can be tuned or affectedby downstream such as MEK1/2, or actin filament polymerization, ordynamin or receptor kinase activity, or upstream signaling molecules,such as certain GPCR agonists including carbachol. The potency ofmodulators that against targets can be also examined using their uniqueDMR signature or effect on the overall DMR signal obtained.

Also disclosed are methods to screen modulators that affect RTKsignaling. The methods comprise: (a) providing an optical-based labelfree biosensor; (b) placing a certain number of cells having a RTK ofinterest in a medium to cover the biosensor such that the cells attachonto the surface of the biosensor; (c) monitoring the cell responseusing the biosensor; (d) applying a solution containing a compound at acertain concentration into the cell medium; (e) applying a solutioncontaining a ligand to the RTK and continuously monitoring the timedependent response of the cells cultured on the biosensor.

(5) Assaying Cholesterol Transport

The correct intracellular distribution of cholesterol among cellularmembranes is essential for many biological functions of mammalian cells,including signal transduction and membrane traffic. The prominent roleof cholesterol in membrane trafficking is increasingly apparent. Forexample, depletion of plasma membrane-localized cholesterol inhibitsclathrin-mediated endocytosis, but vesicular recycling seems unaffected.Since no direct measure of cholesterol is feasible, several indirectmethods have been developed to study intracellular distribution ofcholesterol and lipid signaling. Quenching emission from fluorescentsterols using membrane impermeant quenchers is used to determine thetransbilyar distribution of cholesterol in plasma membranes. However,this approach is not ideal, in part because there may be quantitativedifferences in the properties of the fluorescent cholesterol analogs ascompared with cholesterol. Furthermore, although cholesterol is poorlysoluble in water, cholesterol can spontaneously desorb from membranes atan appreciable rate. Most often it will return to the same membrane, butit can also bind to whatever other hydrophobic binding sites areavailable.

The transport and distribution of newly synthesized cholesterol can bedetermined by introducing 3H-acetate into living cells and measuring theamount of 3H cholesterol in isolated membranes at different times.Radiolabeled cholesterol and cholesterol esters can be delivered bylipoproteins. Total cholesterol can be measured by direct chemicalmethods such as gas chromatography-mass spectrometry or by indirectmethods such as assays based on cholesterol oxidase. In order for any ofthese methods of measuring cholesterol transport and distribution to beused, the various organelles of interest must be purified. It isgenerally quite difficult to obtain highly purified membrane fractions;and lengthy purification protocols may increase the risk of cholesteroltransfer. These methods are most useful when organelles can be easilyseparated, as with the ER and the plasma membrane, but they can be verydifficult to interpret when organelles such as endosomes and Golgimembranes are considered.

Filipin staining has been widely used to detect cholesterol in variousmembrane organelles in intact cells, due to that fact that thisfluorescent detergent binds selectively to cholesterol but not tocholesterol esters. Filipin is a relatively weak fluorophore and can bedetected by cooled charge-coupled device cameras. However, filipinstaining can only provide qualitative information for cholesteroldistribution, since its fluorescence intensity is not necessarilylinearly related to cholesterol content. Another limitation is thatcholesterol might redistribute during long incubations with filipin.Thus, quantification of the intracellular cholesterol distribution fromexperiments using filipin is not possible.

Some specialized techniques, such as the cholesterol oxidase assay, havebeen developed to quantify cholesterol in the plasma membrane. Thisassay will overestimate the amount of cholesterol on the plasma membraneif the enzyme gains access to intracellular compartments (e.g., byendocytosis in living cells or by membrane breakage) or if cholesterolmoves to the plasma membrane during the assay. While many methods havebeen developed to measure cholesterol distribution in cells, all of themare subject to various degrees of uncertainty in their interpretation.It is therefore necessary to compare results obtained by severaldifferent methods in order to get a reliable analysis of intracellularcholesterol distribution.

Cholesterol not only can be transported from one location or compartmentto another in cells. It can also be excreted to outside the cells usinga process called reverse cholesterol transport. The first step inreverse cholesterol transport is the efflux of free cholesterol from theplasma membrane of peripheral cells to an extracellular acceptor. Thismovement of cholesterol is governed by both cellular and extracellularfactors. Many studies have focused on the extracellular acceptors ofcellular cholesterol, specifically how modifications of these acceptorscan positively enhance cholesterol efflux. It is generally believed thatreverse cholesterol transport is mediated by high-density lipoprotein(HDL). With phospholipid-containing acceptors such as HDL, therate-limiting step is the desorption of cholesterol molecules from theplasma membrane.

There are at least two pathways by which cholesterol can be removed fromperipheral cells. Cholesterol acceptors, which already containphospholipids, such as HDL particles or PL-apoA-1 disks, can removecholesterol by diffusion via a concentration gradient between themembrane cholesterol donor and acceptor particle. The aqueous diffusionmodel is therefore a bi-directional mass transport model, which does notrequire the acceptor particle to bind or penetrate the cellular plasmamembrane. The level of expression of the scavenger receptor B type 1(SR-B1) is correlated with rates of cholesterol efflux to HDL orphospholipid particles. The ability of SR-B1 to stimulate cholesterolefflux appears independent of receptor-ligand binding and may reflecteffects on the organization of membrane cholesterol domains thatfacilitate aqueous diffusion of cholesterol to acceptor particles.

Alternatively, lipid-poor cholesterol acceptors such as apoA-1 interactdirectly with the plasma membrane, simultaneously abstracting bothcholesterol and phospholipid. Cholesterol efflux to lipid-free apoA-1 islargely dependent on expression of the ATP binding cassette transporterA1 (ABCA1). While its importance in apoA-1 mediated cholesterol effluxis clear, the exact function of ABCA1 in cholesterol export remainscontroversial, with recent studies suggesting roles as an apoA-1receptor, an intracellular cholesterol transporter or in inducingmodifications to membrane lipid distribution that favor apoA-1 dockingat the cell surface.

The disclosed methods can be used to assay cholesterol transport and to,for example, screen for molecules that effect cholesterol transport,such as effluxing and uptake. FIG. 26 shows an example of a method toscreen modulators that interfere with cholesterol effluxing. This methodis based on the measurement in real time of the effect of compounds oncholesterol effluxing. Depletion of cholesterol content on cell surfaceor intracellular pool results in the disappearance of microvilli locatedin the cell surface, resulting in the flatness of cells adherent on asurface. The flatness of cells leads to a positive DMR phase withincreased signal. Based on this biological effect, we use reagents, asmarkers, that can either extract cholesterol from the cell surface(e.g., methyl-beta-cyclodextrin (mβCD), or high density lipoproteins(HDLs)), or bind or sequester cholesterol on the cell surface (e.g.,saponin at relatively low concentrations). The changes obtained usingoptical biosensors can be used as an indicator of modulators thatinterfere with the cholesterol effluxing. FIG. 27 provides a schematicof a cholesterol pathway.

The results in FIG. 28 showed that mβCD treatment of both A431 and HeLacells gave rise to similar time-dependent responses obtained using LIDbiosensors. The difference between these two cell types is due to thedistinct cholesterol content associated with the cell surface. Thepretreatment of A431 cells with EGF significantly suppressed themβCD-induced response. This is because the binding of EGF to EGFRslocated at the cell surface results in a significant endocytosis of thereceptor; and the receptor endocytosis causes the reduction of cellsurface cholesterol content. Similarly, the pretreatment of A431 cellswith H7, a protein kinase A, C and G inhibitor, also led to thesuppression of the mβCD-induced response. This is because protein kinaseis a critical regulator of cholesterol content on the cell surface.

(6) Assaying Reactive Species Signaling and Cell Redox States

Molecular oxygen (dioxygen; O₂) is essential for the survival of allaerobic organisms. Aerobic energy metabolism is dependent on oxidativephosphorylation, a process by which the oxidoreduction energy ofmitochondrial electron transport (via a multicomponent NADHdehydrogenase enzymatic complex) is converted to the high-energyphosphate bond of ATP. O₂ serves as the final electron acceptor forcytochrome-c oxidase, the terminal enzymatic component of thismitochondrial enzymatic complex, which catalyzes the four-electronreduction of O₂ to H₂O. Partially reduced and highly reactivemetabolites of O₂ may be formed during these (and other) electrontransfer reactions. These O₂ metabolites include superoxide anion (O₂.)and hydrogen peroxide (H₂O₂), formed by one- and two-electron reductionsof O₂, respectively. In the presence of transition metal ions, the evenmore reactive hydroxyl radical (OH.) can be formed. These partiallyreduced metabolites of O₂ are often referred to as “reactive oxygenspecies” (ROS) due to their higher reactivities relative to molecularO₂.

ROS have dual impacts on the cellular functions. ROS are initiallyconsidered as toxic by-products of metabolism with the potential tocause damage to lipids, proteins, and DNA. To protect against thepotentially damaging effects of ROS, cells possess several antioxidantenzymes such as superoxide dismutase (which reduces O₂. to H₂O₂),catalase, and glutathione peroxidase (which reduces H₂O₂ to H₂O). Thusoxidative stress may be broadly defined as an imbalance between oxidantproduction and the antioxidant capacity of the cell to prevent oxidativeinjury. Oxidative stress has been implicated in a large number of humandiseases including atherosclerosis, pulmonary fibrosis, cancer,neurodegenerative diseases, and aging.

Although ROS are generally considered to be toxic by-products ofrespiration, recent evidence suggests that the production of ROS mightbe essential participants in cell signaling and regulation. In mammaliancells, a variety of extracellular stimuli have been shown recently toinduce a transient increase in the intracellular concentration of ROS,and specific inhibition of the ROS generation results in a completeblockage of stimulant-dependent signaling. The downstream effect of ROSproduction is the more or less reversible oxidation of proteins. Thiols,by virtue of their ability to be reversibly oxidized, are recognized askey targets of oxidative stress. Redox-sensitive proteins, which includeprotein tyrosine phosphatases (PTPs) as the active site cysteine, arethe target of specific oxidation by various oxidants, including H₂O₂,and this modification can be reversed by intracellular reducing agents.The inhibition exerted by ROS on PTPs helps the propagation of receptortyrosine kinase (RTK) signals mediated by protein tyrosinephosphorylation, generally associated with the proliferative stimulus.

The apparent paradox in the roles of ROS as essential biomolecules inthe regulation of cellular functions and as toxic by-products ofmetabolism may be, at least in part, related to differences in theconcentrations of ROS produced. When cellular production of ROSoverwhelms its antioxidant capacity, damage to cellular macromoleculessuch as lipids, protein, and DNA may ensue.

The high reactivity and relative instability of ROS make them extremelydifficult to detect or measure in biological systems. Thus assessmentsof ROS and free radical generation have largely been made by indirectmeasurement of various end products resulting from the interaction ofROS with cellular components such as lipids, protein, or DNA. Mostmethods for identification of specific ROS are based on reactions withvarious “detector” molecules (e.g., fluorogenic, chemiluminescent orchromogenic probes) that are oxidatively modified to elicit luminescentor fluorescent signals. Such methods could be complicated by thepossibility of having multiple forms of reactive oxygen in the samecell. In addition, the nitric oxide radical may produce the same changesin the optical properties of the probe as do other reactive oxygenmolecules. Quantitative analysis is also difficult because of: 1) thehigh intracellular concentration of glutathione, which can form thiyl orsulfinyl radicals or otherwise trap or reduce oxygen species; 2) thevariable concentration of metals, which can either catalyze or inhibitradical reactions; and 3) the presence of other free radical-quenchingagents such as spermine.

Disclosed are the methods to monitor in real time the effect ofcompounds on the H₂O₂-induced dynamic mass redistribution (DMR) inliving cells. To study the ROS signaling, a wide array of well-known andspecific modulators for various cellular targets was used to pretreatthe cells for certain time (typically one hour). The ROS signalingnetworks then can be mapped out according to the effect of themodulators on the H₂O₂-induced DMR signals. To screen compounds thatmodulate the cellular redox states, cells are pretreated with compoundsfor long periods of time (typically overnight to days). The effect ofcompounds on the cellular redox states can be examined by theH₂O₂-mediated DMR signals.

Unlike all the existing assay technologies for ROS signaling and redoxstate, the present invention provides a label-free and real time methodto screen modulators that interfere with the ROS signaling and itsnetwork interactions. The present invention also extends theapplications of optical biosensor-based cell sensing.

Cellular production of ROS occurs from both enzymatic and nonenzymaticsources. Any electron-transferring protein or enzymatic system canresult in the formation of ROS as “by-products” of electron transferreactions. The enzymatic sources include:

(i) Cell metabolism in mitochondria. The generation of ROS inmitochondria accounts for 1-2% of total O₂ consumption under reducingconditions. Due to high concentrations of mitochondrial SOD, theintra-mitochondrial concentrations of O₂. are maintained at very lowsteady-state levels, and is unlikely to escape into the cytoplasm. Thepotential for mitochondrial ROS to mediate cell signaling has gainedsignificant attention in recent years, particularly with regard to theregulation of apoptosis. It has also been suggested that themitochondria may function as an “O₂ sensor” to mediate hypoxia-inducedgene transcription.

(ii) Lipid and protein biosynthesis in endoplasmic reticulum (ER). ER isanother membrane-bound intracellular organelle that is primarilyinvolved in lipid and protein biosynthesis. Smooth ER (lacking boundribosomes) contains enzymes including cytochrome P-450 that catalyze aseries of reactions to detoxify lipid-soluble drugs and other harmfulmetabolic products. cytochrome P-450 can oxidize unsaturated fatty acidsand xenobiotics and reduce molecular O₂ to produce O₂. and/or H₂O₂.

(iii) ROS from nuclear membranes. Nuclear membranes contain cytochromeoxidases and electron transport systems that resemble those of the ERbut the function of which is unknown. It has been postulated thatelectron “leaks” from these enzymatic systems may give rise to ROS thatcan damage cellular DNA in vivo.

(iv) H₂O₂ generation in peroxisomes. Peroxisomes are an important sourceof total cellular H₂O₂ production. They contain a number ofH₂O₂-generating enzymes including glycolate oxidase, D-amino acidoxidase, urate oxidase, L-hydroxyacid oxidase, and fatty acyl-CoAoxidase. Peroxisomal catalase utilizes H₂O₂ produced by these oxidasesto oxidize a variety of other substrates in “peroxidative” reactions.These types of oxidative reactions are particularly important in liverand kidney cells in which peroxisomes detoxify a variety of toxicmolecules (including ethanol) that enter the circulation. Another majorfunction of the oxidative reactions carried out in peroxisomes isoxidation of fatty acids, which in mammalian cells occurs inmitochondria and peroxisomes. Only a small fraction of H₂O₂ generated inthese intracellular organelles appears to escape peroxisomal catalase.

(v) ROS from soluble enzymes. Soluble enzymes such as xanthine oxidase,aldehyde oxidase, dihydroprotate dehydrogenase, flavoproteindehydrogenase and tryptophan dioxygenase can generate ROS duringcatalytic cycling.

(vi) ROS from small molecules. Auto-oxidation of small molecules such asdopamine, epinephrine, flavins, and hydroquinones can be an importantsource of intracellular ROS production. In most cases, the directproduct of such autooxidation reactions is O₂—.

(vii) ROS from plasma membrane associated enzymes. Plasmamembrane-associated oxidases (e.g., phagocytic NADPH oxidase) have beenimplicated as the sources of most growth factor- and/orcytokine-stimulated oxidant production, although the precise enzymaticsources have yet to be fully characterized.

(viii) ROS from signaling. A variety of cytokines and growth factorsthat bind receptors of different classes have been reported to generateROS in cells.

(ix) ROS from environment. Exogenous ROS can also be introduced inliving cells. For example, exogenous H₂O₂ is capable of diffusing acrossthe plasma membrane into the cells.

ROS regulates a large number of signaling pathways at multiple levelsfrom receptor to nucleus. Cellular targets, although less clear, havebeen identified and broadened over the past decade. Receptor kinases andphosphatases may be targets of oxidative stress. Growth factor receptorsare most commonly activated by ligand-induced dimerization oroligomerization that autophosphorylates its cytoplasmic kinase domain.Ligand-independent clustering and activation of receptors in response toultraviolet light have also been well demonstrated, and this effectappears to be mediated by ROS. Exogenous H₂O₂ (usually in the millimolarrange) has been shown to induce tyrosine phosphorylation and activationof the PDGF-, PDGF-, and EGF receptors. Lysophatidic acid-inducedtransactivation of the EGF receptor appears to be mediated by theintermediate formation of ROS. Because most growth factors and cytokinesappear to generate ROS at or near the plasma membrane, phospholipidmetabolites are potentially important targets for redox signaling. Forexample, the oxidized forms of diacylglycerol were more effective inactivating PKC than its nonoxidized forms. In addition, PKC activationand protein tyrosine phosphorylation appear to be required forH₂O₂-induced PLD activation in endothelial cells and fibroblasts.Non-RTKs belonging to the Src family (Src kinases) and Janus kinase(JAK) family are also targets, at least, for exogenously added oxidants.

The ROS signaling also is able to trigger changes in intracellular Ca²⁺in a number of cell types including smooth muscle cells. Furthermore,the ROS signaling can participate in MAPK pathway. Exogenous oxidantscan activate the ERK MAPK pathway. The mechanism(s) for this effect isunclear, and the precise molecular target(s) is unknown. Some studiessuggest that ROS-mediated ERK activation may be an upstream event at thelevel of growth factor receptors, Src kinases, and/or p21Ras. Anotherpotential mechanism for this effect may be oxidant-induced inactivationof protein tyrosine phosphatases (PTPs) and/or protein phosphatase A.

There are many other intracellular targets that have been identified asoxidation responsive molecules. These targets include NF-kB (atranscription factor that regulates the expression of a number of genesinvolved in immune and inflammatory responses), activator protein-1(AP-1) (a transcriptional complex formed by the dimerization of Fos-Junor Jun-Jun proteins), and other transcription factors in which DNAbinding is regulated by similar redox mechanisms such as Sp-1, c-Myb,p53 and egr-1.

The ROS signaling primarily involves two general mechanisms ofaction: 1) alterations in intracellular redox state and 2) oxidativemodifications of proteins.

In one embodiment, the present invention provides methods for the use ofan optical biosensor to screen compounds that can interfere with the ROSsignaling. The method involves the use of hydrogen peroxide as exogenousROS to mediate mass redistribution within the bottom portion of culturedcell layer. The method comprise the following steps: Providing anoptical label independent detection (LID) biosensor being capable ofmulti-optical output parameter measurements; Culturing cells onto thesurface of the biosensor; Applying a modulator solution to the cells;Applying an exogenous reactive oxygen species solution to the cells;Monitoring said optical output parameters. The said modulator isselected from a pool of well-characterized modulators of cellulartargets. The said modulator solution is applied and incubated for shortperiod of time with said cells (e.g., 30 min, 60 min, 1 hr, 3 hrs, 6hrs, 24 hrs, 2 days, 3 days, 5 days, etc). The said reactive oxygenspecies is hydrogen peroxide.

6. Additions to Label Free Cell Assays

a) Two Part Assays Using Label Free Biosensors in Conjunction withLabeling Technology

The disclosed label free biosensor cell based assays can also be used inconjunction with conventional label technologies (e.g. fluorescence) toprovide multiparametric information on biological samples.

Label independent detection includes a suite of technologies thatmeasure biomolecular events in a manner that does not require any of theanalytes to be labeled. The two most popular technologies are based onmass spectroscopy (MS) and measurements of changes in refractive index(RI) using techniques such as surface plasmon resonance (SPR) or gratingcoupled waveguides as discussed herein. Disclosed herein is a systemcontaining an instrument coupled to a optical biosensor containingdielectric coated optical gratings for simultaneous measurements ofchanges in refractive index and fluorescence (confocal or evanescentfield).

While RI based label independent detection (RILID) methods offersignificant advantages relative to labeled technologies, a limitation isthat the event cannot be directly correlated to a particular species.For example, unlike fluorescence, binding of the desired protein andsome undesirable protein qualitatively offer the same “type” of signal(change in index). The label free detection method itself is thereforenon-specific in nature. To offset this ambiguity, RILID methods havebeen coupled to MS to enable the identification of the bound species.

RILID measurements can be made in real time, and is typically focused byits ability to typically detect events within ˜200 nm or less of thesubstrate surface and lateral resolution of ˜10 μm. Fluorescence enablesthe labeling of multiple species (with different fluorescent dyes orparticles), and can be used in the evanescent mode (using total internalreflectance fluorescence or grating coupled waveguides) which enablesdetection within ˜200 nm or the confocal mode which enables detectionwithin ˜10 μm, and has excellent lateral resolution (down to ˜300 nm inthe far field or <100 nm in the near field). Disclosed is the use ofRILID as another “channel” for bio-detection using a combination of thetwo technologies, label free biosensors and labeling, both of whichshare time and space resolution but one which is species specific innature (labeling, i.e. fluorescence) and one that is speciesnon-specific in nature (label free biosensors, RILID). This combinationis inherently powerful as it enables one to dissect complexbio-detection events such as those encountered while studying biologicalpathways within cells. For example, the binding of a ligand to areceptor (e.g. a GPCR) can induce cellular cascades that may result in acomplex change in refractive index profile with time. One or more ofthese cascades can be probed by fluorescence using different reportersystems or labeling at the cellular, organelle (e.g. using organellespecific dyes to probe the ER, Golgi, or nucleus), protein (e.g.translocation of GFP-β-arrestin) or DNA level (gene expression usingfluorescence in-situ hybridization, FISH). Correlation of the LID signalto multicolor fluorescence in time and space can offer vital clues aboutthe pathway. Moreover, certain fluorescent reporters and/or labels areoften mutually incompatible. The disclosed methods allow analysis of thecorrelation and can enable assay development such that the need for oneor more fluorescent reporters is removed because that information isavailable through RILID.309. Disclosed are multimode detection systemsutilizing planar waveguide-based biosensors. This system not onlymonitors the refractive index changes, indicated by changes inwavelength or angle of reflected lights induced by a net change inbio-mass upon binding and subsequent activation and cellular responses,but also changes in fluorescence (or chemiluminescence, bioluminescence,phosphorescence or electro-luminescence, etc). Also provided aredetection systems that provide ultra-high content assays for use in drugdiscovery and fundamental research.

Current bioanalytical techniques are typically uniparametric in nature.As a result, outputs from multiple different assays are iteratively puttogether to guide decisions about drug discovery (or diagnosis). Thisprocess can be both time consuming and misleading. Multiparametricdetection seeks to obtain information on several fronts usingcombinations of analytical techniques that provide clues about multiplesteps in a pathway (or multiple pathways) and their modulation bypotential drug compounds. Multiparametric detection is distinct frommultiplexing in that multiplexing implies the simultaneous detection ofbinding to or activation of multiple biological species using onetechnique (or combinations, e.g. combinations of radioactive andfluorescent labels) to monitor the same step in the pathway.Multiparametric detection, in conjunction with multiplexed assays (e.g.reverse transfection arrays) offer the possibility of multiple types ofinformation on multiple samples simultaneously. Grating coupledwaveguides are uniquely advantageous in terms of a platform formultiparametric detection by enabling both RILID and fluorescence.

III. COMPOSITIONS

Disclosed are the components to be used to prepare the disclosedcompositions as well as the compositions themselves to be used withinthe methods disclosed herein. These and other materials are disclosedherein, and it is understood that when combinations, subsets,interactions, groups, etc. of these materials are disclosed that whilespecific reference of each various individual and collectivecombinations and permutation of these compounds may not be explicitlydisclosed, each is specifically contemplated and described herein. Forexample, if a particular receptor is disclosed and discussed and anumber of modifications that can be made to a number of moleculesincluding the receptor are discussed, specifically contemplated is eachand every combination and permutation of receptor and the modificationsthat are possible unless specifically indicated to the contrary. Thus,if a class of molecules A, B, and C are disclosed as well as a class ofmolecules D, E, and F and an example of a combination molecule, A-D isdisclosed, then even if each is not individually recited each isindividually and collectively contemplated meaning combinations, A-E,A-F, B-D, B-E, B-F, C-D, C-E, and C—F are considered disclosed.Likewise, any subset or combination of these is also disclosed. Thus,for example, the sub-group of A-E, B-F, and C-E would be considereddisclosed. This concept applies to all aspects of this applicationincluding, but not limited to, steps in methods of making and using thedisclosed compositions. Thus, if there are a variety of additional stepsthat can be performed it is understood that each of these additionalsteps can be performed with any specific embodiment or combination ofembodiments of the disclosed methods.

1. Compositions Identified by Screening with DisclosedCompositions/Combinatorial Chemistry

a) Combinatorial Chemistry

The disclosed compositions can be used as targets for any combinatorialtechnique to identify molecules or macromolecular molecules thatinteract with the disclosed compositions in a desired way. The nucleicacids, peptides, and related molecules disclosed herein can be used astargets for the combinatorial approaches. Also disclosed are thecompositions that are identified through combinatorial techniques orscreening techniques in which the compositions disclosed in herein orportions thereof, are used as the target in a combinatorial or screeningprotocol.

It is understood that when using the disclosed compositions incombinatorial techniques or screening methods, molecules, such asmacromolecular molecules, will be identified that have particulardesired properties such as inhibition or stimulation or the targetmolecule's function. The molecules identified and isolated when usingthe disclosed compositions, such as, the disclosed cells, are alsodisclosed. Thus, the products produced using the combinatorial orscreening approaches that involve the disclosed compositions, such as,the disclosed cells, are also considered herein disclosed.

It is understood that the disclosed methods for identifying molecules asdiscussed herein can be performed using high through put means. Forexample, putative inhibitors can be identified using FluorescenceResonance Energy Transfer (FRET) to quickly identify interactions. Theunderlying theory of the techniques is that when two molecules are closein space, ie, interacting at a level beyond background, a signal isproduced or a signal can be quenched. Then, a variety of experiments canbe performed, including, for example, adding in a putative inhibitor. Ifthe inhibitor competes with the interaction between the two signalingmolecules, the signals will be removed from each other in space, andthis will cause a decrease or an increase in the signal, depending onthe type of signal used. This decrease or increasing signal can becorrelated to the presence or absence of the putative inhibitor. Anysignaling means can be used. For example, disclosed are methods ofidentifying an inhibitor of the interaction between any two of thedisclosed molecules comprising, contacting a first molecule and a secondmolecule together in the presence of a putative inhibitor, wherein thefirst molecule or second molecule comprises a fluorescence donor,wherein the first or second molecule, typically the molecule notcomprising the donor, comprises a fluorescence acceptor; and measuringFluorescence Resonance Energy Transfer (FRET), in the presence of theputative inhibitor and the in absence of the putative inhibitor, whereina decrease in FRET in the presence of the putative inhibitor as comparedto FRET measurement in its absence indicates the putative inhibitorinhibits binding between the two molecules. This type of method can beperformed with a cell system as well.

Oligonucleotide molecules with a given function, catalytic orligand-binding, can be isolated from a complex mixture of randomoligonucleotides in what has been referred to as “in vitro genetics”(Szostak, TIBS 19:89, 1992). One synthesizes a large pool of moleculesbearing random and defined sequences and subjects that complex mixture,for example, approximately 10¹⁵ individual sequences in 100 μg of a 100nucleotide RNA, to some selection and enrichment process. Throughrepeated cycles of affinity chromatography and PCR amplification of themolecules bound to the ligand on the column, Ellington and Szostak(1990) estimated that 1 in 10¹⁰ RNA molecules folded in such a way as tobind a small molecule dyes. DNA molecules with such ligand-bindingbehavior have been isolated as well (Ellington and Szostak, 1992; Bocket al, 1992). Techniques aimed at similar goals exist for small organicmolecules, proteins, antibodies and other macromolecules known to thoseof skill in the art. Screening sets of molecules for a desired activitywhether based on small organic libraries, oligonucleotides, orantibodies is broadly referred to as combinatorial chemistry.Combinatorial techniques are particularly suited for defining bindinginteractions between molecules and for isolating molecules that have aspecific binding activity, often called aptamers when the macromoleculesare nucleic acids.

There are a number of methods for isolating proteins which either havede novo activity or a modified activity. For example, phage displaylibraries have been used to isolate numerous peptides that interact witha specific target. (See for example, U.S. Pat. Nos. 6,031,071;5,824,520; 5,596,079; and 5,565,332 which are herein incorporated byreference at least for their material related to phage display andmethods relate to combinatorial chemistry)

A preferred method for isolating proteins that have a given function isdescribed by Roberts and Szostak (Roberts R. W. and Szostak J. W. Proc.Natl. Acad. Sci. USA, 94(23)12997-302 (1997). This combinatorialchemistry method couples the functional power of proteins and thegenetic power of nucleic acids. An RNA molecule is generated in which apuromycin molecule is covalently attached to the 3′-end of the RNAmolecule. An in vitro translation of this modified RNA molecule causesthe correct protein, encoded by the RNA to be translated. In addition,because of the attachment of the puromycin, a peptidyl acceptor whichcannot be extended, the growing peptide chain is attached to thepuromycin which is attached to the RNA. Thus, the protein molecule isattached to the genetic material that encodes it. Normal in vitroselection procedures can now be done to isolate functional peptides.Once the selection procedure for peptide function is completetraditional nucleic acid manipulation procedures are performed toamplify the nucleic acid that codes for the selected functionalpeptides. After amplification of the genetic material, new RNA istranscribed with puromycin at the 3′-end, new peptide is translated andanother functional round of selection is performed. Thus, proteinselection can be performed in an iterative manner just like nucleic acidselection techniques. The peptide which is translated is controlled bythe sequence of the RNA attached to the puromycin. This sequence can beanything from a random sequence engineered for optimum translation (i.e.no stop codons etc.) or it can be a degenerate sequence of a known RNAmolecule to look for improved or altered function of a known peptide.The conditions for nucleic acid amplification and in vitro translationare well known to those of ordinary skill in the art and are preferablyperformed as in Roberts and Szostak (Roberts R. W. and Szostak J. W.Proc. Natl. Acad. Sci. USA, 94(23)12997-302 (1997)).

Another preferred method for combinatorial methods designed to isolatepeptides is described in Cohen et al. (Cohen B. A., et al., Proc. Natl.Acad. Sci. USA 95(24):14272-7 (1998)). This method utilizes and modifiestwo-hybrid technology. Yeast two-hybrid systems are useful for thedetection and analysis of protein:protein interactions. The two-hybridsystem, initially described in the yeast Saccharomyces cerevisiae, is apowerful molecular genetic technique for identifying new regulatorymolecules, specific to the protein of interest (Fields and Song, Nature340:245-6 (1989)). Cohen et al., modified this technology so that novelinteractions between synthetic or engineered peptide sequences could beidentified which bind a molecule of choice. The benefit of this type oftechnology is that the selection is done in an intracellularenvironment. The method utilizes a library of peptide molecules thatattached to an acidic activation domain. Using methodology well known tothose of skill in the art, in combination with various combinatoriallibraries, one can isolate and characterize those small molecules ormacromolecules, which bind to or interact with the desired target. Therelative binding affinity of these compounds can be compared and optimumcompounds identified using competitive binding studies, which are wellknown to those of skill in the art.

Techniques for making combinatorial libraries and screeningcombinatorial libraries to isolate molecules which bind a desired targetare well known to those of skill in the art. Representative techniquesand methods can be found in but are not limited to U.S. Pat. Nos.5,084,824, 5,288,514, 5,449,754, 5,506,337, 5,539,083, 5,545,568,5,556,762, 5,565,324, 5,565,332, 5,573,905, 5,618,825, 5,619,680,5,627,210, 5,646,285, 5,663,046, 5,670,326, 5,677,195, 5,683,899,5,688,696, 5,688,997, 5,698,685, 5,712,146, 5,721,099, 5,723,598,5,741,713, 5,792,431, 5,807,683, 5,807,754, 5,821,130, 5,831,014,5,834,195, 5,834,318, 5,834,588, 5,840,500, 5,847,150, 5,856,107,5,856,496, 5,859,190, 5,864,010, 5,874,443, 5,877,214, 5,880,972,5,886,126, 5,886,127, 5,891,737, 5,916,899, 5,919,955, 5,925,527,5,939,268, 5,942,387, 5,945,070, 5,948,696, 5,958,702, 5,958,792,5,962,337, 5,965,719, 5,972,719, 5,976,894, 5,980,704, 5,985,356,5,999,086, 6,001,579, 6,004,617, 6,008,321, 6,017,768, 6,025,371,6,030,917, 6,040,193, 6,045,671, 6,045,755, 6,060,596, and 6,061,636.

Combinatorial libraries can be made from a wide array of molecules usinga number of different synthetic techniques. For example, librariescontaining fused 2,4-pyrimidinediones (U.S. Pat. No. 6,025,371)dihydrobenzopyrans (U.S. Pat. Nos. 6,017,768 and 5,821,130), amidealcohols (U.S. Pat. No. 5,976,894), hydroxy-amino acid amides (U.S. Pat.No. 5,972,719) carbohydrates (U.S. Pat. No. 5,965,719),1,4-benzodiazepin-2,5-diones (U.S. Pat. No. 5,962,337), cyclics (U.S.Pat. No. 5,958,792), biaryl amino acid amides (U.S. Pat. No. 5,948,696),thiophenes (U.S. Pat. No. 5,942,387), tricyclic Tetrahydroquinolines(U.S. Pat. No. 5,925,527), benzofurans (U.S. Pat. No. 5,919,955),isoquinolines (U.S. Pat. No. 5,916,899), hydantoin and thiohydantoin(U.S. Pat. No. 5,859,190), indoles (U.S. Pat. No. 5,856,496),imidazol-pyrido-indole and imidazol-pyrido-benzothiophenes (U.S. Pat.No. 5,856,107) substituted 2-methylene-2,3-dihydrothiazoles (U.S. Pat.No. 5,847,150), quinolines (U.S. Pat. No. 5,840,500), PNA (U.S. Pat. No.5,831,014), containing tags (U.S. Pat. No. 5,721,099), polyketides (U.S.Pat. No. 5,712,146), morpholino-subunits (U.S. Pat. Nos. 5,698,685 and5,506,337), sulfamides (U.S. Pat. No. 5,618,825), and benzodiazepines(U.S. Pat. No. 5,288,514).

As used herein combinatorial methods and libraries included traditionalscreening methods and libraries as well as methods and libraries used ininteractive processes.

b) Computer Assisted Drug Design

The disclosed compositions can be used as targets for any molecularmodeling technique to identify either the structure of the disclosedcompositions or to identify potential or actual molecules, such as smallmolecules, which interact in a desired way with the disclosedcompositions. The nucleic acids, peptides, and related moleculesdisclosed herein can be used as targets in any molecular modelingprogram or approach.

It is understood that when using the disclosed compositions in modelingtechniques, molecules, such as macromolecular molecules, will beidentified that have particular desired properties such as inhibition orstimulation or the target molecule's function. The molecules identifiedand isolated when using the disclosed compositions, such as, thedisclosed cells, are also disclosed. Thus, the products produced usingthe molecular modeling approaches that involve the disclosedcompositions, such as, the disclosed cells, are also considered hereindisclosed.

Thus, one way to isolate molecules that bind a molecule of choice isthrough rational design. This is achieved through structural informationand computer modeling. Computer modeling technology allows visualizationof the three-dimensional atomic structure of a selected molecule and therational design of new compounds that will interact with the molecule.The three-dimensional construct typically depends on data from x-raycrystallographic analyses or NMR imaging of the selected molecule. Themolecular dynamics require force field data. The computer graphicssystems enable prediction of how a new compound will link to the targetmolecule and allow experimental manipulation of the structures of thecompound and target molecule to perfect binding specificity. Predictionof what the molecule-compound interaction will be when small changes aremade in one or both requires molecular mechanics software andcomputationally intensive computers, usually coupled with user-friendly,menu-driven interfaces between the molecular design program and theuser.

Examples of molecular modeling systems are the CHARMm and QUANTAprograms, Polygen Corporation, Waltham, Mass. CHARMm performs the energyminimization and molecular dynamics functions. QUANTA performs theconstruction, graphic modeling and analysis of molecular structure.QUANTA allows interactive construction, modification, visualization, andanalysis of the behavior of molecules with each other.

A number of articles review computer modeling of drugs interactive withspecific proteins, such as Rotivinen, et al., 1988 Acta PharmaceuticaFennica 97, 159-166; Ripka, New Scientist 54-57 (Jun. 16, 1988);McKinaly and Rossmann, 1989 Annu. Rev. Pharmacol. Toxiciol 29, 111-122;Perry and Davies, QSAR: Quantitative Structure-Activity Relationships inDrug Design pp. 189-193 (Alan R. Liss, Inc. 1989); Lewis and Dean, 1989Proc. R. Soc. Lond. 236, 125-140 and 141-162; and, with respect to amodel enzyme for nucleic acid components, Askew, et al., 1989 J. Am.Chem. Soc. 111, 1082-1090. Other computer programs that screen andgraphically depict chemicals are available from companies such asBioDesign, Inc., Pasadena, Calif., Allelix, Inc, Mississauga, Ontario,Canada, and Hypercube, Inc., Cambridge, Ontario. Although these areprimarily designed for application to drugs specific to particularproteins, they can be adapted to design of molecules specificallyinteracting with specific regions of DNA or RNA, once that region isidentified.

Although described above with reference to design and generation ofcompounds which could alter binding, one could also screen libraries ofknown compounds, including natural products or synthetic chemicals, andbiologically active materials, including proteins, for compounds whichalter substrate binding or enzymatic activity.

Kits

Disclosed herein are kits that are drawn to reagents that can be used inpracticing the methods disclosed herein. The kits can include anyreagent or combination of reagent discussed herein or that would beunderstood to be required or beneficial in the practice of the disclosedmethods. For example, the kits could include primers to perform theamplification reactions discussed in certain embodiments of the methods,as well as the buffers and enzymes required to use the primers asintended.

IV. METHODS OF MAKING THE COMPOSITIONS

The compositions disclosed herein and the compositions necessary toperform the disclosed methods can be made using any method known tothose of skill in the art for that particular reagent or compound unlessotherwise specifically noted.

Nucleic Acid Synthesis

For example, the nucleic acids, such as, the oligonucleotides to be usedas primers can be made using standard chemical synthesis methods or canbe produced using enzymatic methods or any other known method. Suchmethods can range from standard enzymatic digestion followed bynucleotide fragment isolation (see for example, Sambrook et al.,Molecular Cloning: A Laboratory Manual, 2nd Edition (Cold Spring HarborLaboratory Press, Cold Spring Harbor, N.Y., 1989) Chapters 5, 6) topurely synthetic methods, for example, by the cyanoethyl phosphoramiditemethod using a Milligen or Beckman System 1Plus DNA synthesizer (forexample, Model 8700 automated synthesizer of Milligen-Biosearch,Burlington, Mass. or ABI Model 380B). Synthetic methods useful formaking oligonucleotides are also described by Ikuta et al., Ann. Rev.Biochem. 53:323-356 (1984), (phosphotriester and phosphite-triestermethods), and Narang et al., Methods Enzymol., 65:610-620 (1980),(phosphotriester method). Protein nucleic acid molecules can be madeusing known methods such as those described by Nielsen et al.,Bioconjug. Chem. 5:3-7 (1994).

2. Peptide Synthesis

One method of producing the disclosed proteins, such as SEQ ID NO:23, isto link two or more peptides or polypeptides together by proteinchemistry techniques. For example, peptides or polypeptides can bechemically synthesized using currently available laboratory equipmentusing either Fmoc (9-fluorenylmethyloxycarbonyl) or Boc(tert-butyloxycarbonoyl) chemistry. (Applied Biosystems, Inc., FosterCity, Calif.). One skilled in the art can readily appreciate that apeptide or polypeptide corresponding to the disclosed proteins, forexample, can be synthesized by standard chemical reactions. For example,a peptide or polypeptide can be synthesized and not cleaved from itssynthesis resin whereas the other fragment of a peptide or protein canbe synthesized and subsequently cleaved from the resin, thereby exposinga terminal group which is functionally blocked on the other fragment. Bypeptide condensation reactions, these two fragments can be covalentlyjoined via a peptide bond at their carboxyl and amino termini,respectively, to form an antibody, or fragment thereof. (Grant G A(1992) Synthetic Peptides: A User Guide. W.H. Freeman and Co., N.Y.(1992); Bodansky M. and Trost B., Ed. (1993) Principles of PeptideSynthesis. Springer-Verlag Inc., NY (which is herein incorporated byreference at least for material related to peptide synthesis).Alternatively, the peptide or polypeptide is independently synthesizedin vivo as described herein. Once isolated, these independent peptidesor polypeptides may be linked to form a peptide or fragment thereof viasimilar peptide condensation reactions.

For example, enzymatic ligation of cloned or synthetic peptide segmentsallow relatively short peptide fragments to be joined to produce largerpeptide fragments, polypeptides or whole protein domains (Abrahmsen L etal., Biochemistry, 30:4151 (1991)). Alternatively, native chemicalligation of synthetic peptides can be utilized to syntheticallyconstruct large peptides or polypeptides from shorter peptide fragments.This method consists of a two step chemical reaction (Dawson et al.Synthesis of Proteins by Native Chemical Ligation. Science, 266:776-779(1994)). The first step is the chemoselective reaction of an unprotectedsynthetic peptide—thioester with another unprotected peptide segmentcontaining an amino-terminal Cys residue to give a thioester-linkedintermediate as the initial covalent product. Without a change in thereaction conditions, this intermediate undergoes spontaneous, rapidintramolecular reaction to form a native peptide bond at the ligationsite (Baggiolini M et al. (1992) FEBS Lett. 307:97-101; Clark-Lewis I etal., J. Biol. Chem., 269:16075 (1994); Clark-Lewis I et al.,Biochemistry, 30:3128 (1991); Rajarathnam K et al., Biochemistry33:6623-30 (1994)).

Alternatively, unprotected peptide segments are chemically linked wherethe bond formed between the peptide segments as a result of the chemicalligation is an unnatural (non-peptide) bond (Schnolzer, M et al.Science, 256:221 (1992)). This technique has been used to synthesizeanalogs of protein domains as well as large amounts of relatively pureproteins with full biological activity (deLisle Milton R C et al.,Techniques in Protein Chemistry IV. Academic Press, New York, pp.257-267 (1992)).

3. Process Claims for Making the Compositions

Disclosed are processes for making the compositions as well as makingthe intermediates leading to the compositions. There are a variety ofmethods that can be used for making these compositions, such assynthetic chemical methods and standard molecular biology methods. It isunderstood that the methods of making these and the other disclosedcompositions are specifically disclosed. Disclosed are cells produced bythe process of transforming the cell with any of the disclosed nucleicacids. Disclosed are cells produced by the process of transforming thecell with any of the non-naturally occurring disclosed nucleic acids.

Disclosed are any of the disclosed peptides produced by the process ofexpressing any of the disclosed nucleic acids. Disclosed are any of thenon-naturally occurring disclosed peptides produced by the process ofexpressing any of the disclosed nucleic acids. Disclosed are any of thedisclosed peptides produced by the process of expressing any of thenon-naturally disclosed nucleic acids.

Disclosed are animals produced by the process of transfecting a cellwithin the animal with any of the nucleic acid molecules disclosedherein. Disclosed are animals produced by the process of transfecting acell within the animal any of the nucleic acid molecules disclosedherein, wherein the animal is a mammal. Also disclosed are animalsproduced by the process of transfecting a cell within the animal any ofthe nucleic acid molecules disclosed herein, wherein the mammal ismouse, rat, rabbit, cow, sheep, pig, or primate.

Also disclose are animals produced by the process of adding to theanimal any of the cells disclosed herein.

V. METHODS OF USING THE COMPOSITIONS

1. Methods of Using the Compositions as Research Tools

The disclosed compositions can be used as discussed herein as eitherreagents in micro arrays or as reagents to probe or analyze existingmicroarrays. The disclosed compositions can be used in any known methodfor isolating or identifying single nucleotide polymorphisms. Thecompositions can also be used in any known method of screening assays,related to chip/micro arrays. The compositions can also be used in anyknown way of using the computer readable embodiments of the disclosedcompositions, for example, to study relatedness or to perform molecularmodeling analysis related to the disclosed compositions.

VI. ILLUSTRATIONS OF CERTAIN EMBODIMENTS

Disclosed is a method to test a stimulatory event's effect on a cellcomprising providing a label free biosensor, culturing a cell on thebiosensor, providing a stimulatory event to the cultured cell,collecting biosensor output data from the biosensor.

Also disclosed is a method to screen compounds that affect cellviability or proliferation based on inhomogeneity of cells on thesurface of a biosensor.

A method to screen modulators that affect a stimulatory event's effecton a cell comprising providing a label free biosensor, culturing a cellon the biosensor, incubating with a solution containing a compound for aspecific and predetermined time, providing a stimulatory event to thecultured cell, collecting biosensor output data from the biosensor.

Also disclosed is a method for analyzing a cell comprising providing adetection system, provide a plurality of biosensors, placing cells inmedium, culturing the cells on the biosensor to a confluency of at least70%, applying a compound solution, measuring the angle or wavelength ofincidence that coupling in the biosensor occurs, wherein, themeasurement occurs in less than 10 minutes.

Also disclosed is a method for monitoring a compound toxicity,comprising: (a) providing an optical-based label free biosensor; (b)placing a cell in a medium, wherein the cell attaches onto the surfaceof the biosensor; (c) applying a solution containing a compound into thecell medium; (d) and monitoring the response of the cells cultured onthe biosensor.

Also disclosed is a method for monitoring the effect of a compound on acell comprising, (a) incubating the cell with the compound, wherein thecell is attached to a label free biosensor, (b) identifying the effectthe compound has on the cell, wherein the step of identifying comprisesobserving and analyzing the output of the label free biosensor.

Also disclosed is a method for monitoring the effect of a compound on acell comprising, (a) incubating the cell with the compound, wherein thecell is attached to a label free biosensor, (b) identifying the effectthe compound has on the cell, wherein the step of identifying comprisesobserving the output of the label free biosensor, and wherein the outputis compared to a signature output.

Also disclosed is a method for monitoring the compound adsorption andtoxicity in real time, comprising the steps: (a) providing anoptical-based label free biosensor; (b) placing a certain number ofcells in a medium to cover the biosensor such that the cells attach ontothe surface of the biosensor; (c) applying a solution containing acompound into the cell medium; (e) and monitoring the time dependentresponse of the cells cultured on the biosensor.

Also disclosed is a method of identifying a state of a cell, the methodcomprising the steps, (a) culturing the cell on a surface of a biosensorforming a cell-biosensor composition, (b) assaying the cell-biosensorcomposition, wherein the step of assaying comprises identifying aninhomogeneity of the surface where the cell is cultured.

Also disclosed is a method for high throughput screening of compoundtoxicity on cells using a biosensor, comprising the steps of: (a)providing a biosensor; (b) placing cells into each well to cover thebiosensor such that the cells attach and reach high confluency onto thesurface of the biosensor; (c) applying a compound solution into the cellmedium of each well; (d) collecting optical waveguide lightmode spectraat a certain time, (e) comparing the PWHM of each compound with acontrol well wherein the cells are not exposed to any compound, whereinthe toxicity of compounds can be evaluated using a single data point.

Also disclosed is a method to evaluate compound toxicity comprising, (a)providing an optical based label free biosensor attached to a microplatewith wells; (b) placing cells into each well along with a cell medium,wherein the cells cover the biosensor such that the cells attach ontothe surface of the biosensor; (c) applying a compound solution into thecell medium of each well; (d) collecting images of a TM₀ mode resonanceangular band of the whole sensor area of each well at a designated time.

Also disclosed is a method for high throughput screening of a compoundfor the compound's effect on cell proliferation using opticalbiosensors, comprising (a) providing a biosensor; (b) bringing a cell incontact with the biosensor forming a cell-biosensor composition suchthat after a period of time for cell growth the cell confluency reaches45%-55%, (c) incubating the compound with the cell-biosensorcomposition, forming a compound-cell-biosensor complex, (d) collectingthe output of the biosensor, (d) obtaining a PWHM from the output, (e)comparing the PWHM of each compound-cell-biosensor complex with acontrol wherein the cell-biosensor composition is not exposed to thecompound, wherein a decrease in the PWHM indicates the compound has aneffect on the cell.

Also disclosed is a method for monitoring ligand binding and asequential signaling event in cells in real time, which comprises: (a)providing an optical-based label free biosensor; (b) placing cellshaving a receptor tyrosine kinase (RTK) on the sensor surface; the cellsare suspended in a medium containing certain concentration of serumwhich is required for the attachment and growth of the cells on thebiosensor surface; (c) optionally incubating the cells with a mediumwithout serum or other growth factors, or without any serum or othergrowth factors for overnight in order to reach quiescent states of thecells; (d) placing the biosensors having a layer of the cells into thedetection system and monitoring the response; (e) monitoring the timedependent response of the layer of the adherent cells before and afteraddition of a solution containing a stimulus or sequential addition oftwo solutions, the first one containing a compound and the second onecontaining a ligand or marker, separated by a specific period of time.

Also disclosed is a method for measuring or determining the expressionlevel and cell-surface expression level of receptor tyrosine kinases(RTK) in cells, which comprises: (a) providing a microplate withmultiple wells, each well having an optical-based label free biosensorembedded in the bottom; (b) providing multiple types of cells; (c)placing one type of cell suspended in a medium into at least one well;(d) culturing the cells in an appropriate medium for attachment andgrowth until a certain level of confluence is reached; (e) placing themicroplate having biosensors, each biosensor covered by a layer of thecells into a detection system and monitoring the response; (f) applyinga solution containing a ligand to the RTK into the medium; (g)monitoring and comparing the time dependent response of the layer ofdifferent types of cells.

Also disclosed is a method for determining the potency of ligand's to anRTK which comprises: (a) providing a microplate with multiple wells,each well having an optical-based label free biosensor embedded in thebottom; (b) providing a certain number of cells having relatively highexpression level of an RTK in a medium such that the cells becomeattached to each biosensor with a desired confluence; (c) exchanging themedium to starve the adherent cells for certain time; (d) placing themicroplate having biosensors, each biosensor covered by a layer of thecells into a to detection system and monitoring the response; (f)applying a solution containing a ligand at different concentrations intothe medium covering each biosensor; (g) monitoring and comparing thedose- and time-dependent response of the cells.

Also disclosed is a method for screening modulators that affect receptortyrosine kinase (RTK) signaling comprising: (a) providing anoptical-based label free biosensor; (b) placing a certain number ofcells having a RTK of interest in a medium to cover the biosensor suchthat the cells attach onto the surface of the biosensor; (c) monitoringthe cell response using the biosensor; (d) applying a solutioncontaining a compound at a certain concentration into the cell medium;(e) applying a solution containing a ligand to the RTK and continuouslymonitoring the time dependent response of the cells cultured on thebiosensor.

Also disclosed is a method for analyzing cytoskeleton arrangement incells the method comprising providing an optical label independentdetection (LID) biosensor and monitoring release of bio-materials fromcells adherent on a surface of the optical LID biosensor.

Also disclosed is a method for analyzing cytoskeleton rearrangementcomprising, providing the optical LID biosensor; placing the livingcells in a cell medium to cover the optical LID biosensor so the livingcells are able to attach to the surface of the optical LID biosensor;applying a solution containing a pore-forming reagent into the cellmedium located on the surface of the optical LID biosensor; andinterrogating the optical LID biosensor to obtain a time dependentoptical response which indicates the loss of biomaterials from thecells.

Also disclosed is a method of analyzing cytoskeleton structurecomprising providing the optical LID biosensor; placing living cells ina cell medium to cover the optical LID biosensor so the living cells areable to attach to the surface of the optical LID biosensor; applying asolution containing a compound into the cell medium located on thesurface of the optical LID biosensor; applying a solution containing apore-forming reagent solution into the cell medium located on thesurface of the optical LID biosensor; and interrogating the optical LIDbiosensor to obtain a time dependent optical response which indicatesthe loss of biomaterials from the cells that enables one to screenmodulators capable of interfering with the cytoskeleton structure withincells.

Also disclosed is a method of analyzing cytoskeleton structurecomprising providing the optical LID biosensor; placing the living cellsin a cell medium to cover the optical LID biosensor so the living cellsare able to attach to the surface of the optical LID biosensor; applyinga solution containing a pore-forming reagent solution into the cellmedium located on the surface of the optical LID biosensor; applying asolution containing a compound into the cell medium located on thesurface of the optical LID biosensor; and interrogating the optical LIDbiosensor to obtain a time dependent optical response which indicatesthe loss of biomaterials from the cells that enables one to screenmodulators capable of interfering with the cytoskeleton structure withincells.

Disclosed are methods to test the effect of a stimulatory event on acell comprising providing a label free biosensor, incubating a cell onthe biosensor, providing a stimulatory event to the incubated cell,collecting biosensor output from the biosensor.

Also disclosed are methods of identifying a state of a cell, the methodcomprising culturing the cell on a surface of a label free biosensorforming a cell-biosensor composition, and assaying the cell-biosensorcomposition, wherein the assaying comprises identifying an inhomogeneityof the surface where the cell is cultured.

Also disclosed are methods that can include methods wherein incubating acell involves culturing the cell, wherein a stimulatory effect isidentified from the biosensor output.

Also disclosed are methods that can include methods wherein the cell iscultured to 20-99% confluency, wherein the cell is cultured to 30-80%confluency, wherein the cell is cultured to 40-65% confluency, whereinthe cell is cultured to 70-99% confluency, and wherein the cell iscultured to 80-95% confluency.

Also disclosed are methods that can include methods wherein the cell isan adherent cell, wherein the cell is in contact with the biosensor,wherein the cell attaches to the biosensor.

Also disclosed are methods that can include, wherein the stimulatoryevent comprises adding a compound to the cell culture, wherein thecompound modulates a cell signaling pathway of the cell, wherein themodulation activates the cell signaling pathway, wherein the modulationsuppresses the cell signaling pathway, wherein the compound modulates acell surface receptor on the cell, wherein the compound is an agonist ofthe receptor, and wherein the compound is an antagonist of the receptor.

Also disclosed are methods that can include methods wherein the cellsurface receptor is an ion channel, a receptor tyrosine kinase, acytokine receptor, an integrin receptor, a Na⁺/H⁺ exchanger receptor, oran immune receptor, wherein the cell surface receptor is a G proteincoupled receptor (GPCR), Epidermal growth factor receptor, (EGFR),Platelet derived growth factor receptor (PDGFR), Fibroblast growthfactor receptor (FGF), or Vascular endothelial growth factor receptor(VEGFR), wherein the compound modulates a cytoskeleton component withinthe cell, wherein the compound destabilizes the cytoskeleton structure,wherein the compound stabilizes the cytoskeleton structure, wherein thecompound modulates an intracellular enzyme, an intracellular kinase, anintracellular organelle, an intracellular protein, or an extracellularmatrix, wherein the compound is added in a compound solution.

Also disclosed are methods that can include further comprisingdetermining if the compound is toxic to the cell.

Also disclosed are methods that can include methods wherein a pluralityof compounds are tested to screen for compounds that are toxic to thecell, wherein the level of toxicity of the compound is monitored via thebiosensor output.

Also disclosed are methods that can include, wherein the cell ismonitored via the biosensor output for an effect of the compound.

Also disclosed are methods that can include methods wherein absorptionof the compound is monitored via the biosensor output.

Also disclosed are methods that can include methods wherein thebiosensor can penetrate the cell to a depth of 100 nm, wherein thebiosensor can penetrate the cell to a depth of 100 nm, 200 nm, 300, or500 nm, wherein the biosensor can receive data from multiple depths ofpenetration within the cell, wherein the depths of penetration are up to500 nm.

Also disclosed are methods that can include methods wherein the state ofthe cell is identified using the biosensor output.

Also disclosed are methods that can include further comprisingdetermining if the stimulatory event affects cell viability orproliferation.

Also disclosed are methods that can include methods wherein a pluralityof compounds are tested to screen for compounds that are toxic to thecell, wherein the effect of the compound on the cell is monitored,wherein the compound is an anticancer compound.

Also disclosed are methods that can include methods wherein collectingbiosensor output from the biosensor comprises collecting a biosensoroutput parameter.

Also disclosed are methods that can include methods wherein thebiosensor output parameter is a parameter related to the kinetics of thebiosensor output.

Also disclosed are methods that can include methods wherein thebiosensor output parameter comprises analyzing the overall kinetics ofthe biosensor output, wherein the analyzing of the overall kineticscomprises analyzing the rate of change from one phase to another phaseat the completion of a phase transition, wherein the analyzing of theoverall kinetics comprises analyzing the length of time it takes tocomplete output of the biosensor output, wherein the analyzing of theoverall kinetics comprises analyzing the length of time for which anoverall phase of the output of the biosensor output takes, wherein theanalyzing of the overall kinetics comprises analyzing the total durationof a P-DMR phase, wherein the analyzing of the overall kineticscomprises analyzing the total duration of an N-DMR phase, wherein theanalyzing of the overall kinetics comprises analyzing the rate forattaining the total amplitude of the P-DMR, wherein the analyzing of theoverall kinetics comprises analyzing the rate for attaining the totalamplitude of the N-DMR, wherein the analyzing of the overall kineticscomprises analyzing the rate to go from a N-DMR to a P-DMR, wherein theanalyzing of the overall kinetics comprises analyzing the transitiontime t from a P-DMR phase to a N-DMR phase, a net-zero phase to a P-DMRphase, a net-zero to a N-DMR phase, a net-zero to a P-DMR phase, a P-DMRphase to a net-zero phase, a N-DMR phase to a net zero, or a P-DMR to anet-zero.

Also disclosed are methods that can include methods wherein thebiosensor output parameter comprises analyzing the phases of thebiosensor output, wherein the analyzing the phases comprises analyzing aphase transition, wherein the analyzing the phases comprises analyzing aPositive-Directional Mass Redistribution (P-DMR) signal, wherein theanalyzing the phases comprises analyzing a Negative-Directional MassRedistribution (N-DMR) signal, wherein the analyzing the phasescomprises analyzing a net-zero Directional Mass Redistribution (net-zeroDMR), wherein the analyzing the phases comprises analyzing the shape ofa Positive-Directional Mass Redistribution (P-DMR) signal, wherein theanalyzing the phases comprises analyzing the amplitude of aPositive-Directional Mass Redistribution (P-DMR) signal, wherein theanalyzing the phases comprises analyzing the shape of aNegative-Directional Mass Redistribution (N-DMR) signal, and wherein theanalyzing the phases comprises analyzing the amplitude of aNegative-Directional Mass Redistribution (N-DMR) signal.

Also disclosed are methods that can include methods wherein thebiosensor output parameter comprises the overall dynamics of thebiosensor output, wherein the analyzing overall dynamics comprisesanalyzing the shape of the complete curve produced by the biosensoroutput.

Also disclosed are methods that can include methods wherein thebiosensor output parameter is a parameter related to the resonant peak.

Also disclosed are methods that can include methods wherein thebiosensor output parameter comprises analyzing the intensity of thelight versus the angle of incidence at which the light is coupled intothe biosensor.

Also disclosed are methods that can include methods wherein thebiosensor output parameter comprises analyzing the intensity of thelight versus the wavelength of light at which the light is coupled intothe biosensor.

Also disclosed are methods that can include methods wherein thebiosensor output parameter comprises analyzing the peak position.

Also disclosed are methods that can include methods wherein analyzingthe peak position comprises analyzing the position of the half maximalpeak intensity occurring before the position of the maximal intensity.

Also disclosed are methods that can include methods wherein analyzingthe peak position comprises analyzing the position of the half maximalpeak intensity occurring after the position of the maximal intensity.

Also disclosed are methods that can include methods wherein thebiosensor output parameter comprises analyzing the intensity of a pointon the resonant peak.

Also disclosed are methods that can include methods wherein analyzingthe intensity of the resonant peak comprises analyzing the intensity ofthe maximal intensity.

Also disclosed are methods that can include methods wherein analyzingthe intensity of the resonant peak comprises analyzing the intensity ofthe half maximal peak intensity that occurs on the resonant peak priorto the peak intensity.

Also disclosed are methods that can include methods wherein analyzingthe intensity of the resonant peak comprises analyzing the intensity ofthe half maximal peak intensity that occurs on the resonant peak afterthe peak intensity.

Also disclosed are methods that can include methods wherein the methodfurther comprises collecting a second biosensor output parameter.

Also disclosed are methods that can include methods wherein the secondbiosensor output parameter comprises analyzing peak position.

Also disclosed are methods that can include methods wherein thebiosensor output parameter comprises analyzing the peak shape.

Also disclosed are methods that can include methods wherein analyzingthe peak shape comprises determining the area beneath the resonant peak.

Also disclosed are methods that can include methods wherein the areabeneath the resonant peak only includes the area above a line drawnbetween the half maximal intensity points occurring on the resonantpeak.

Also disclosed are methods that can include methods wherein analyzingthe peak shape comprises analyzing the width of the resonant peak at thehalf maximal intensity points.

Also disclosed are methods that can include methods wherein thebiosensor output parameter is a parameter related to the resonant bandimage.

Also disclosed are methods that can include methods wherein the resonantband image is obtained by illuminating the biosensor with a light spotacross the biosensor and imaging in-coupled light intensity distributionacross the biosensor.

Also disclosed are methods that can include methods wherein thein-coupled light intensity distribution is imaged with a CCD camera.

Also disclosed are methods that can include methods wherein theparameter related to the resonant band image is the band shape, the bandposition, the band intensity, or the light intensity distribution.

Also disclosed are methods that can include methods wherein the peakwidth at half maximum (PWHM) in combination with the position of themaximum intensity are analyzed.

Also disclosed are methods that can include further comprisingincubating the cultured cell with a compound.

Also disclosed are methods that can include further comprisingdetermining if the compound affects the effect of the stimulatory eventon the cell.

Also disclosed are methods that can include further comprisingdetermining the affect of the compound on the effect of the stimulatoryevent on the cell.

Also disclosed are methods that can include methods wherein one or moreadditional compounds are screened to determining if the compounds affectthe effect of the stimulatory event on the cell.

Also disclosed are methods that can include methods wherein biosensoroutput is collected for less than 10 minutes, and wherein biosensoroutput is collected for less than 5 minutes, 1 minute, 30 seconds, 10seconds, 5 seconds, or 1 second.

Also disclosed are methods that can include methods wherein biosensoroutput is collected for a time substantially the same as the biologicaldiffusion limit for the stimulatory effect.

Also disclosed are methods that can include further comprising providinga detection system.

Also disclosed are methods that can include methods wherein a pluralityof label free biosensors are provided, wherein a cell is cultured oneach of two or more of the biosensors, wherein a stimulatory event isprovided to the two or more biosensors, wherein biosensor output iscollected from the two of more biosensors.

Also disclosed are methods that can include methods wherein amultiplicity of penetration depths of the cell are monitored.

Also disclosed are methods that can include methods wherein eachbiosensor has one of the penetration depths.

Also disclosed are methods that can include methods wherein thebiosensor outputs from the two or more biosensors are collectedsimultaneously.

Also disclosed are methods that can include methods wherein the cellsare cultured simultaneously.

Also disclosed are methods that can include methods wherein thestimulatory events are provided to the two or more biosensorssimultaneously.

Also disclosed are methods that can include methods wherein a pluralityof different cells types is incubated on the plurality of biosensors.

Also disclosed are methods that can include methods wherein theplurality of cells comprises at least two cells that are differentbecause at least one of the cells has been genetically engineered.

Also disclosed are methods that can include methods wherein each celltype within the plurality of cell type is detected by a differentbiosensor of the plurality of biosensors.

Also disclosed are methods that can include methods wherein the cell iscultured to a confluency of at least 70%.

Also disclosed are methods that can include methods wherein the cellcomprises a plurality of cells.

Also disclosed are methods that can include further comprising applyinga buffer solution to the cell, wherein the buffer solution is compatiblewith the type of cell and type of stimulatory event.

Also disclosed are methods that can include methods wherein collectingbiosensor output comprises exposing the biosensor to light at varyingangles of incidence and measuring the angle of incidence at which thelight becomes in-coupled.

Also disclosed are methods that can include methods wherein collectingbiosensor output comprises exposing the biosensor to light of varyingwavelengths and measuring the wavelength at which the light becomesin-coupled.

Also disclosed are methods that can include methods wherein the cell isin a proliferating state, in a quiescent state, in a differentiatedstate, or in a specific cell cycle state.

Also disclosed are methods that can include methods wherein the cell isin a proliferating state by culturing the cell with a growth medium.

Also disclosed are methods that can include methods wherein the cell isin a quiescent state by culturing the cell with a starvation medium.

Also disclosed are methods that can include further comprising analyzingthe biosensor output.

Also disclosed are methods that can include methods wherein themonitoring occurs continuously with a sampling rate of 1 second, 3seconds, 5 seconds, 10 seconds, 20 seconds, 30 seconds, 1 minute or 5minutes.

Also disclosed are methods that can include further comprisingidentifying the effect of the stimulatory event on the cell.

Also disclosed are methods that can include methods wherein identifyingthe effect comprises comparing the biosensor output to a signatureoutput.

Also disclosed are methods that can include methods wherein thesignature output comprises a dynamic mass redistribution responsecomprising at least one of the phases: positive-DMR, negative-DMR andnet-zero DMR phases.

Also disclosed are methods that can include methods wherein the cellarises from a cell line.

Also disclosed are methods that can include methods wherein the cellline is a genetically engineered variant cell line.

Also disclosed are methods that can include methods wherein thestimulatory event comprises adding a compound to the cell culture,wherein the effect is an effect on absorption, distribution, metabolism,or toxicity of the compound on the cell.

Also disclosed are methods that can include methods wherein thestimulatory event comprises adding a compound to the cell culture,wherein determining the effect of the compound comprises a functionalassessment of the effect of the compound on the cell and identificationof the effect of the compound on absorption, distribution, metabolism,excretion, or toxicity on the cell.

Also disclosed are methods that can include methods wherein the outputof the biosensor is correlated with a change in mass redistribution withthe cell.

Also disclosed are methods that can include methods wherein the outputof the biosensor is observable as an angular or spectral change in areflected beam of the biosensor.

Also disclosed are methods that can include methods wherein collectingthe biosensor output comprises monitoring the time dependent response ofthe cultured cell.

Also disclosed are methods that can include methods wherein the cellsreached at least 80% confluence.

Also disclosed are methods that can include methods wherein thebiosensor is embedded in a microplate.

Also disclosed are methods that can include methods wherein the cellsare grown on the biosensor for at least 1 hour, 5 hours, 10 hours, 16hours, 24 hours, 36 hours, a week, or two weeks.

Also disclosed are methods that can include methods wherein thebiosensor is capable of differentiating between an area of the biosensorsurface in contact with a viable cell, an area of the biosensor surfacein contact with a cell that has been affected by a stimulatory event,and an area of the biosensor surface contacting no cell.

Also disclosed are methods that can include methods wherein the affectedcell has ejected a portion of its intracellular components or is a deadcell.

Also disclosed are methods that can include further comprisingincubating the cell-biosensor composition with a compound.

Also disclosed are methods that can include methods wherein the compoundis a chemical, a biochemical, a biological molecule, a drug, or apolymer.

Also disclosed are methods that can include methods wherein the assayingis performed after incubating with the compound.

Also disclosed are methods that can include methods wherein the assayingoccurs in less than or equal to 60 seconds, 45 seconds, 30 seconds, 15seconds, 10 seconds, 5 seconds, 4 seconds, 3 seconds, 2 seconds, or 1second.

Also disclosed are methods that can include methods wherein theinhomogeneity is determined by collecting biosensor output from thebiosensor, wherein the biosensor output comprises a resonant peak of aguided mode having a maximum intensity, and comparing the width of thepeak at half-maximum intensity (PWHM).

Also disclosed are methods that can include methods wherein the guidedmode is a transverse magnetic mode.

Also disclosed are methods that can include methods wherein thebiosensor is in a singular or multiplexed format.

Also disclosed are methods that can include methods wherein when thebiosensor is in a multiplexed format, wherein the biosensor is embeddedin one or more wells of a microplate.

Also disclosed are methods that can include methods wherein there is onebiosensor in one well of a microplate.

Also disclosed are methods that can include methods wherein there aremultiple biosensors in one well of a microplate, wherein the biosensorsare physically separated with or without a barrier.

Also disclosed are methods that can include methods wherein thebiosensors are physically separated with a barrier, wherein the barrierthat defines the compartment within the well is lower than the barrierdefining the well in the microplate.

Also disclosed are methods that can include methods wherein thebiosensor is an optical waveguide biosensor.

Also disclosed are methods that can include methods wherein thebiosensor is an optical waveguide grating biosensor.

Also disclosed are methods that can include methods wherein a cell iscultured in each of two or more wells, wherein a stimulatory event isprovided to the two or more wells, wherein the stimulatory eventcomprises adding a compound to the two or more wells, wherein biosensoroutput is collected from the two of more wells, wherein the PWHM of twoor more of the wells is compared with a control well, wherein astimulatory event is not provided to the control well.

Also disclosed are methods that can include methods wherein thebiosensor output is collected at a rate greater than 1, 2, 3, 4, 5, 10,15, 30, 45, or 60 second(s) per well.

Also disclosed are methods that can include methods wherein thebiosensor output is a rate greater than 60, 30, 15, 10, 7, 5, 4, 3, 2,or 1 well(s) per minute.

Also disclosed are methods that can include methods wherein the PWHM ofthe wells is compared at a rate greater than 1, 2, 3, 4, 5, 10, 15, 30,45, or 60 second(s) per well.

Also disclosed are methods that can include methods wherein the PWHM ofthe wells is compared a rate greater than 60, 30, 15, 10, 7, 5, 4, 3, 2,or 1 well(s) per minute.

Also disclosed are methods that can include methods wherein the toxicityof the compounds can be evaluated using a single data point.

Also disclosed are methods that can include methods wherein thebiosensor output are time-dependent PWHM changes.

Also disclosed are methods that can include methods wherein thebiosensor is an optical biosensor.

Also disclosed are methods that can include methods wherein thebiosensor is an optical based biosensor.

Also disclosed are methods that can include methods wherein thebiosensor is a label free biosensor

Also disclosed are methods that can include methods wherein thebiosensor is attached to a system for culturing cells.

Also disclosed are methods that can include methods wherein the systemis a plate.

Also disclosed are methods that can include methods wherein the plate isa plate with a plurality of wells.

Also disclosed are methods that can include methods wherein the plate isa microplate.

Also disclosed are methods that can include methods wherein a cell iscultured in each of two or more wells, wherein a microplate is comprisedof the wells, wherein the biosensor output is images of a TM₀ moderesonance angular band of the whole sensor area of each well at adesignated time.

Also disclosed are methods that can include methods wherein the cellsreach 70% confluency.

Also disclosed are methods that can include methods wherein thestimulatory event comprises adding a compound to two or more of thewells, wherein the width of the TM₀ mode resonance angular band iscompared with the width of the TM₀ mode resonance angular band of a wellhaving compound added to the TM₀ mode resonance angular band of a wellwith no compound added.

Also disclosed are methods that can include methods wherein thebiosensor is a waveguide-based biosensor.

Also disclosed are methods that can include methods wherein thewaveguide-based bio sensor is a Nb₂O₅-based optical bio sensor.

Also disclosed are methods that can include methods wherein the cellsare adherent cells.

Also disclosed are methods that can include methods wherein the cellsare grown to a confluency of 30%, 50%, or 90%.

Also disclosed are methods that can include methods wherein thebiosensor output is an optical waveguide lightmode spectra (OWLS), aresonant peak of a guided mode, or a resonant band image of a guidedmode.

Also disclosed are methods that can include methods wherein a decreasein the PWHM indicates that the compound is toxic to the cell.

Also disclosed are methods that can include methods wherein thebroadening of the PWHM indicates that the compound is toxic to the cell.

Also disclosed are methods that can include methods wherein thesplitting of the PWHM indicates that the compound is toxic to the cell.

Also disclosed are methods that can include methods wherein resonanceband broadening indicates the compound is toxic to the cell.

Also disclosed are methods that can include methods wherein the cellsreached a confluency of at least 70%.

Also disclosed are methods that can include methods wherein a decreasein the PWHM indicates the compound has an effect on the cell.

Also disclosed are methods that can include methods wherein thebiosensor is attached to a microplate.

Also disclosed are methods that can include methods wherein thebiosensor is embedded in the bottom of each well of the microplate.

Also disclosed are methods that can include methods wherein thebiosensor is an optical-based label free biosensor.

Also disclosed are methods that can include methods wherein thecell-biosensor is covered with the compound.

Also disclosed are methods that can include methods wherein the compoundis in solution.

Also disclosed are methods that can include methods wherein the numberof starting cells allows for an analysis of either an increase inproliferation or a decrease in proliferation.

Also disclosed are methods that can include methods wherein the numberof cells reach a confluency between 30-70% in the absence of compound.

Also disclosed are methods that can include methods wherein the numberof cells reach a confluency between 40-60%.

Also disclosed are methods that can include methods wherein the numberof cells reach a confluency between 45-55%.

Also disclosed are methods that can include methods wherein the numberof cells reach a confluency of 50%.

Also disclosed are methods that can include methods wherein the numberof cells cultured on the biosensor before incubation with the compoundcomprises at least 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000,10,000, 11,000, 12,000, 13,000, 14,000, 15,000, 16,000, 17,000, 18,000,19,000, 20,000, 21,000, 22,000, 23,000, 24,000, 25,000, 30,000, 35,000,40,000, 45,000, 50,000, 55,000, 60,000, 65,000, or 70,000 cell(s).

Also disclosed are methods that can include methods wherein thebiosensor output is collected at a single time point.

Also disclosed are methods that can include methods wherein thebiosensor output collected is a spectra.

Also disclosed are methods that can include methods wherein thebiosensor output collected is an image of TM₀ mode resonance angularband of the whole individual biosensor area.

Also disclosed are methods that can include methods wherein thebiosensor output collected is an image of TM₀ mode resonance angularband of the whole individual biosensor area.

Also disclosed are methods that can include methods wherein thebiosensor output comprises total angular shift, wherein a decrease inthe total angular shift indicates the compound is an inhibitor of cellproliferation.

Also disclosed are methods that can include methods wherein thebiosensor output comprises total angular shift, wherein an increase inthe total angular shift indicates the compound is an inhibitor of cellproliferation.

Also disclosed are methods that can include methods wherein thebiosensor output comprises the intensity of incoupled light, wherein theintensity of incoupled light is plotted as a function of the angle ofincidence of light.

Also disclosed are methods that can include methods wherein the cellsare cultured on the biosensor for at least 1 hour, 5 hours, 10 hours, 16hours, 24 hours, 36 hours, a week, or two weeks.

Also disclosed are methods that can include methods wherein thebiosensor output comprises a coupling mode.

Also disclosed are methods that can include methods wherein the couplingmode is a transverse magnetic mode (TM₀).

Also disclosed are methods that can include methods wherein the TM₀ modeis plotted as a function of initial cell seeding numbers.

Also disclosed are methods that can include methods wherein the cell hasa receptor tyrosine kinase (RTK), wherein the cell is suspended in amedium containing serum at a concentration that allows for theattachment and growth of the cell on the biosensor surface, wherein thecell adheres to the biosensor surface.

Also disclosed are methods that can include further comprising starvingthe adherent cell by culturing the cell in starvation medium at 37° C.,wherein the starvation medium is a medium containing low concentrationof serum.

Also disclosed are methods that can include further comprising applyinga buffer solution at least once into the medium.

Also disclosed are methods that can include methods wherein thestimulatory event comprises applying a ligand to the RTK into themedium.

Also disclosed are methods that can include methods wherein the mediumlacks PDGF (platelet-derived growth factor), EGF, insulin, TGF-α,insulin-like growth factor I (IGF-I), and nerve growth factor (NGF).

Also disclosed are methods that can include methods wherein thestarvation medium has a concentration less than about 0.1% of serum orfetal bovine serum (FBS).

Also disclosed are methods that can include methods wherein thetime-dependent response occurs for at least 1, 2, 3, 4, 5, 6, 7, 8, 9,10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 36, or 48hours.

Also disclosed are methods that can include methods wherein thebiosensor is embedded in the bottom of a microplate having a pluralityof wells, wherein a different type of cell is cultured in each of two ormore wells, wherein a stimulatory event is provided to the two or morewells, wherein the stimulatory event comprises adding a ligand to theRTK to the two or more wells, wherein biosensor output is collected fromthe two of more wells, wherein the biosensor output is thetime-dependent response of the different types of cell.

Also disclosed are methods that can include methods wherein thedifferent types of cell require different culture conditions.

Also disclosed are methods that can include methods wherein theexpression level or cell-surface expression level of the RTK is measuredor determined in the different types of cells.

Also disclosed are methods that can include further comprisingincubating the cultured cell with a compound and determining if thecompound modulates signaling of the RTK.

Also disclosed are methods that can include methods wherein the cell hasa relatively high expression level of the RTK, wherein the biosensor isembedded in the bottom of a microplate having a plurality of wells,wherein a cell is cultured in each of two or more wells, wherein astimulatory event is provided to the two or more wells, wherein thestimulatory event comprises adding a ligand to the RTK to the two ormore wells, wherein a different concentration of the ligand to the RTKis added to the two or more cells, wherein biosensor output is collectedfrom the two of more wells, wherein the biosensor output is the dose-and time-dependent response of the cells in the different wells.

Also disclosed are methods that can include methods wherein the dose-and time-dependent response of the cells is compared.

Also disclosed are methods that can include methods wherein the potencyof the ligand is determined.

Also disclosed are methods that can include further comprising analyzingthe biosensor output for release of biomaterials from the cell, wherebythe state of the cytoskeleton in the cell is analyzed.

Also disclosed are methods that can include methods wherein the releaseof biomaterials from the cell is dependent on a pore-formingreagent-induced permeability of the cells.

Also disclosed are methods that can include further comprising applyinga pore-forming reagent to the cell culture.

Also disclosed are methods that can include methods wherein thebiosensor output is a time dependent optical response.

Also disclosed are methods that can include methods wherein saidpore-forming reagent is a chemical or biological compound that canresult in the pore formation in cell surface membranes.

Also disclosed are methods that can include methods wherein thepore-forming reagent is saponin, digitonin, filipin, or streptolysin O.

Also disclosed are methods that can include further comprising applyinga compound to the cell culture following application of the pore-formingreagent to the cell culture.

Also disclosed are methods that can include methods wherein one or moreadditional compounds are screened to determining if the compounds arecapable of interfering with the cytoskeleton structure within cells.

Also disclosed are methods that can include further comprising applyinga compound to the cell culture prior to application of the pore-formingreagent to the cell culture.

Also disclosed are methods that can include methods wherein one or moreadditional compounds are screened to determining if the compounds arecapable of interfering with the cytoskeleton structure within cells.

Also disclosed are methods that can include further comprising the stepof detecting a label with a device capable of detecting the label.

Also disclosed are methods that can include methods wherein the label isa fluorescent label, a radioactive label, or a phosphorescent label.

Also disclosed are methods that can include methods wherein the step ofdetecting the label occurs simultaneously with the step of monitoringthe biosensor.

Also disclosed are methods that can include methods wherein thebiosensor has two regions, the first one having no material-containingmixture deposited and the second one having material-containing mixturedeposited, such that when the cells are incubated onto the sensor, thecells overlaid the second region become transfected by the materials.

Also disclosed are methods that can include methods wherein the materialis a target gene, a target protein, a fusion protein of the targetprotein and a tag protein, a RNAi against the target, an antibodyagainst the target, an antisense oligonucleotide and its derivates, anantigene oligonucleotide and its derivates.

Also disclosed are methods that can include methods wherein the tagprotein is a His-tag, a GFP protein or one a derivate.

Also disclosed are methods that can include methods wherein the materialis complexed with a reagent such that the cells can uptake the material,when the cells adhere onto the material-presenting region of the sensor.

Also disclosed are methods that can include methods wherein the regionsare formed by selectively depositing the material-containing mixtureonto one half of the sensor surface along the grating structure.

Also disclosed are methods of determining a state of a living cellcomprising observing the dynamic mass redistribution of the cellularcontents, wherein the step of observing occurs on a resonant waveguidegrating biosensor.

Also disclosed are methods for testing a compounds effect on a cellcomprising, culturing cells on a biosensor, first washing the cells,starving the cells, incubating the compound with the cell, and recordinga signal with a biosensor.

Also disclosed are methods 605 further comprising the step of rinsingwith a buffer after the step of starving, or wherein the cells are grownto greater than 90% confluency, or wherein the cells are washed washtwice, or wherein starving cells comprises culturing them only in DMEM,or wherein starving the cells occurs 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40hours, or wherein starving the cells occurs overnight, or wherein therinsing buffer comprises 1× regular Hank's balanced salt solution, 20 mMHEPES buffer, pH 7.0 in the presence of 2.5 mM probenicid, or whereinthe signal is a calcium signal, or wherein calcium signal was recordedwas recorded over 6 minutes with a 6 sec interval, or wherein thebiosensor comprises a HTS7000 BioAssay Reader, or wherein the methodoccurs at room temperature, or wherein the biosensor is a Corning® Epic™angular interrogation system, or wherein the biosensors is used intransverse magnetic mode, or wherein the biosensor is used inp-polarized TM₀ mode, or wherein the compounds were diluted in rinsingbuffer, or wherein the rinsing buffer comprises 1× regular Hank'sbalanced salt solution, 20 mM HEPES buffer, pH 7.0, or wherein thestarving of the cells occurs in a buffer lacking FBS, or wherein thecompound is in a solution wherein the solution has less than 0.05% DMSO,or wherein the step of starving takes place at 37 degrees celcius, orwherein the step of starving further takes place under air/5% CO₂, orwherein cell is pretreated with a compound solution lacking the compoundbefore incubating the compound solution with the cells, until a steadyphase is reached, or wherein the biosensor identifies a change in apixel density of the central position of the resonant band, or whereinthe biosensor measures the angular shift of the resonant band, orfurther comprising the step of plotting the biosensor data as a functionof time, or wherein an increased signal (P-DMR) means an increase in theamount of bio-molecules within the sensing volume and a decreased signal(N-DMR) means a decrease in the amount of bio-molecules within thesensing volume, or wherein the method identifies a signature for thecell and compound, or wherein the signature comprises a P-DMR phasefollowed by a subsequent N-DMR phase, wherein the P-DMR phase occurs ata rate higher than the rate of decay of the N-DMR phase, or wherein thesignature comprises a P-DMR phase until it the P-DMR phase reaches anevaluated plateau, or wherein the signature comprises two consecutiveP-DMR events, wherein the first P-DMR phase to an elevated level occursat a rate greater than the rate the second P-DMR phase occurs to asecond elevated level, or wherein the signature does not include any DMRsignal above the noise level, or further comprising the step of plottingthe signal from the biosensor as a function of the compoundconcentration.

The cell can be cultured to 20-99% confluency, 30-80% confluency, 40-65%confluency, 70-99% confluency, and 80-95% confluency. The cell can beadherent cell. Adherent cells are cells that can adhere on the surfaceof a biosensor. The stimulatory event can comprise adding a compound tothe cell culture. The compound can modulate a cell signaling pathway ofthe cell. The modulation can activate the cell signaling pathway. Themodulation can suppress the cell signaling pathway. The compound canmodulate a cell surface receptor on the cell. The compound modulationcan be an agonist of the receptor. The compound modulation can be anantagonist of the receptor. The cell surface receptor can be a G proteincoupled receptor (GPCR), an ion channel, a receptor tyrosine kinase, acytokine receptor, an integrin receptor, a Na⁺/H⁺ exchanger receptor,and an immune receptor. The receptor tyrosine kinase can be an epidermalgrowth factor receptor (EGFR), a platelet derived growth factor receptor(PDGFR), a fibroblast growth factor receptor (FGF), an insulin receptor,a vascular endothelial growth factor receptor (VEGFR).

The compound can modulate a cytoskeleton component within the cell. Themodulator can destabilize the cytoskeleton structure. The modulator canstabilize the cytoskeleton structure. The compound can modulate anintracellular enzyme, an intracellular kinase, an intracellularorganelle, or an intracellular protein. The compound can modulate anextracellular matrix.

The step of collecting biosensor output data from the biosensor cancomprise collecting a biosensor output data parameter. The biosensoroutput data parameter can be a parameter related to the kinetics of thestimulatory event. The biosensor output parameter can comprise analyzingthe overall kinetics of the biosensor output data. The analyzing of theoverall kinetics can comprise analyzing the rate of the completion ofthe phase transitions. The analyzing of the overall kinetics cancomprise analyzing the length of time it takes to complete data output.The analyzing of the overall kinetics can comprise analyzing the lengthof time for which an overall phase of the data output takes. Theanalyzing of the overall kinetics can comprise analyzing the totalduration of time of a P-DMR phase. The analyzing of the overall kineticscan comprise analyzing the total duration of time of an N-DMR phase. Theanalyzing of the overall kinetics can comprise analyzing the rate foracquiring the total amplitude of the P-DMR. The analyzing of the overallkinetics can comprise analyzing the total length of time it takes forthe total amplitude of the N-DMR. The analyzing of the overall kineticscan comprise analyzing the total length of time it takes for the totalamplitude of the P-DMR. The analyzing of the overall kinetics cancomprise analyzing the transition time τ from a P— to N-DMR phase.

The biosensor output parameter can comprise analyzing the phases of thebiosensor output data. The analyzing the phase can comprise analyzing aphase transition. The analyzing the phase can comprise analyzing aPositive-Directional Mass Redistribution (P-DMR) signal. The analyzingthe phase can comprise analyzing a Negative-Directional MassRedistribution (N-DMR) signal. The analyzing the phase can compriseanalyzing a net-zero Directional Mass Redistribution (net-zero DMR). Theanalyzing the phase can comprise analyzing the shape of aPositive-Directional Mass Redistribution (P-DMR) signal. The analyzingthe phase can comprise analyzing the amplitude a of Positive-DirectionalMass Redistribution (P-DMR) signal. The analyzing the phase can compriseanalyzing the shape of a Negative-Directional Mass Redistribution(N-DMR) signal. The analyzing the phase can comprise analyzing theamplitude a of Negative-Directional Mass Redistribution (N-DMR) signal.

The biosensor output parameter can comprise the overall dynamics of thebiosensor output data. The analyzing overall dynamics can compriseanalyzing the shape of the complete curve produced by the output data.The biosensor output data parameter can be a parameter related to theresonant peak. The biosensor output parameter an comprise analyzing theintensity of the light versus the angle of incidence wherein the lightis coupled into the biosensor. The biosensor output parameter cancomprise analyzing the intensity of the light versus the wavelength oflight wherein the light is coupled into the biosensor. The biosensoroutput parameter can comprise analyzing the peak position. Analyzing thepeak position can comprise analyzing the position of the half maximalpeak intensity occurring before the position of the peak intensity.Analyzing the peak position can comprise analyzing the position of thehalf maximal peak intensity occurring after the position of the peakintensity.

The biosensor output parameter can comprise analyzing the intensity of apoint of the resonant peak. Analyzing the intensity of the resonant peakcan comprise analyzing the intensity of the peak intensity. Analyzingthe intensity of the resonant peak can comprise analyzing the intensityof the half maximal peak intensity that occurs on the resonant peakprior to the peak intensity. Analyzing the intensity of the resonantpeak can comprise analyzing the intensity of the half maximal peakintensity that occurs on the resonant peak after the peak intensity.

The method can further comprise a second biosensor output parameter. Thesecond biosensor output parameter can comprise analyzing peak position.The biosensor output parameter can comprise analyzing the peak shape.Analyzing the peak shape can comprise determining the area beneath theresonant peak. The area beneath the resonant peak can include only thearea above a line drawn between the half maximal intensity pointsoccurring on the resonant peak. Analyzing the peak shape can compriseanalyzing the width of the resonant peak at the half maximal intensitypoints. The biosensor output data parameter can be a parameter relatedto the resonant band image. The resonant band image can be collected byilluminating the sensor with a light spot that across the sensor incombination with a receive system to image the in-coupled lightintensity distribution across the sensor. The receive system can be aCCD camera. The parameter relating to the resonant band image can be theband shape, the band position, the band intensity, or the lightintensity distribution.

The PWHM in combination with the position of the maximum intensity canbe analyzed. The biosensors can be analyzed simultaneously. The time forcollecting a data point from each well biosensor can be done in lessthan 1 hour, 30 min, 5 min, 1 min, 30 sec, 10 sec, 5 second, 2 seconds,1 second, and where it is biological diffusion limited. The cell can beat a proliferating state by culturing the cell with a growth medium, ora quiescent state by culturing the cell with a starvation medium, or adifferentiated state, or a specific cell cycle state. A starvationmedium is any medium which decreases the cell proliferation capacity ofa culture of cells.

The method can further comprise the step of applying a buffer solutionat least once into the cell medium, wherein the buffer solution used canbe based on the optimal assay according to the nature of cell type andof target-compound interaction. The monitoring can occur in continuousfashion with a sampling rate of 1 sec, 3 sec, 5 sec, 10 sec, 20 sec, 30sec, 1 minute, or 5 minutes, 30 minutes. The signature output cancomprise a dynamic mass redistribution response comprising at least oneof the three phases: positive-DMR, negative-DMR and net-zero DMR phases.The cell can arise from a cell line or a genetically engineered variantcell line. The effect of the compound can be determined for an analysisof the adsorption, distribution, metabolism and toxicity of the compoundon a cell. The effect can comprise a functional assessment of thecompound on the cell and identifies the effect of the adsorption,distribution, metabolism, excretion and toxicity on the cell.

The output of the biosensor can be correlated with a change in massredistribution with the cell. The output of the biosensor can beobservable as an angular or spectral change in a reflected beam of thebiosensor. The method can further comprise applying a buffer solution atleast once into the cell medium. The compound can be an anticancercompound, or a potential anticancer compound. There can be at least10×10⁵ cells on the biosensor. The cells can reach at least 80%confluence. The biosensor can be embedded in a microplate. The cells canbe grown on the biosensor for at least 1 hour, 5 hours, 16 hours, 24hours, 36 hours, a week, or two weeks. The biosensor can be capable ofdifferentiating between an area of the biosensor surface in contact witha viable cell. The effected cell can have ejected a portion of itsintracellular components, or can be a dead cell.

The method can further comprise incubating the cell-biosensorcomposition with a compound. The compound is a chemical, a biochemical,a biological, a drug, or a polymer. The method can further compriseperforming the assay step after incubating with the compound. Theassaying can occur in less than or equal to 60, 45, 30, 15, 10, 5, 4, 3,2, or 1 second(s). The inhomogeneity can be determined by collecting anoutput which produces a resonant peak of a guided mode having a maximumintensity and comparing the width of the peak at half-maximum intensity(PWHM). The guided mode can be transverse magnetic mode.

The biosensor can be in a singular or multiplexed format. When thebiosensor is in a multiplexed format, the biosensor can be embedded insome of wells of a microplate. There can be one biosensor in one well ofa microplate. There can be multiple biosensors in one well of amicroplate, in which biosensors can be physically separated with orwithout a barrier. When there is a physically barrier, the barrierdefining the compartment within a well can be lower that that definingthe well in a microplate. The biosensor can be an optical waveguidebiosensor. The biosensor can be an optical waveguide grating biosensor.

The method can further comprise collecting time-dependent PWHM changes.The optical waveguide lightmode spectra can be a resonant peak of aguided transverse magnetic mode. The biosensor can be an opticalbiosensor. The biosensor can be an optical based biosensor. Thebiosensor can be a label free biosensor. The biosensor can be attachedto a system for culturing cells. The system can be a plate. The platecan be a plate with a plurality of wells. The plate can be a microplate.The cells can reach 70% confluency.

The method can further comprise the step of obtaining the width of theTM₀ mode resonance angular band and comparing the width of the TM₀ moderesonance angular band of a well having a compound applied to the TM₀mode resonance angular band of a well with no compound applied. Thebiosensor can be a waveguide-based biosensor. The waveguide-basedbiosensor can be a Nb₂O₅-based optical biosensor. The cells can beadherent cells. The cells can be grown to a confluency of 30%, 50%, or90%. The output can be an optical waveguide lightmode spectra (OWLS), ora resonant peak of a guided mode, or a resonant band image of a guidedmode. A change in the PWHM can indicate that the compound is toxic tothe cell. The broadening of the PWHM can indicate that the compound istoxic to the cell. The splitting of the PWHM can indicate that thecompound is toxic to the cell. Resonance band broadening can indicatethe compound is toxic to the cell. The cells can reach a confluency ofat least 70%. The biosensor can be attached to a microplate. Thebiosensor can be embedded in the bottom of each well of the microplate.The biosensor can be an optical-based label free biosensor. Thecell-biosensor can be covered with the compound. The compound can be insolution. The number of starting cells can allow for an analysis ofeither an increase in proliferation or a decrease in proliferation. Thenumber of cells can reach a confluency between 30-70% in the absence ofcompound. The number of cells can reach a confluency between 40-60%. Thenumber of cells can reach a confluency between 45-55%. The number ofcells can reach a confluency of 50%. The number of cells cultured on thebiosensor before incubation with the compound can comprise at least1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10,000, 11,000,12,000, 13,000, 14,000, 15,000, 16,000, 17,000, 18,000, 19,000, 20,000,21,000, 22,000, 23,000, 24,000, 25,000, 30,000, 35,000, 40,000, 45,000,50,000, 55,000, 60,000, 65,000, or 70,000 cell(s).

The output can be collected at a single time point. The output collectedcan be a spectra. The output collected can be an image of TM₀ moderesonance angular band of the whole individual biosensor area. Theoutput collected can be an image of TM₀ mode resonance angular band ofthe whole individual biosensor area. The method can further compriseobtaining an output providing total angular shift, wherein a decrease inthe total angular shift can indicate the compound is an inhibitor ofcell proliferation. The method can further comprise obtaining an outputproviding total angular shift, wherein an increase in the total angularshift can indicate the compound is an inhibitor of cell proliferation.The output collected can obtain the intensity of incoupled light andplots this a function of the incident angle of light. The cells can becultured on the biosensor for at least 1 hour, 5 hours, 10 hours, 16hours, 24 hours, 36 hours, or overnight.

The output can comprise a coupling mode. The coupling mode can be atransverse magnetic mode (TM₀). The TM₀ mode can be further plotted as afunction of initial cell seeding numbers. The method can furthercomprise starving the adherent cells in a medium containing lowconcentration of serum for certain time at 37° C. The method can furthercomprise applying a buffer solution at least once into the cell mediumfor a certain amount of time. The method can further comprise applying asolution containing a ligand to the RTK into the medium. The cellculture medium can lack PDGF (platelet-derived growth factor), EGF,insulin, TGF-α, insulin-like growth factor I (IGF-I), and nerve growthfactor (NGF). The starvation medium can have a concentration less thanabout 0.1% of serum or bovine serum albumin (BSA). The collection of thebiosensor output can occur for at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 36, or 48 hours.The different types of cells can require different culture conditions.The monitoring release of bio-materials from cells can be dependent on apore-forming reagent-induced permeability of the cells. The pore-formingreagent can be a chemical or biological that can result in the poreformation in cell surface membranes. The pore-forming reagent can besaponin, digitonin, filipin, or streptolysin O.

VII. EXAMPLES

The following examples are put forth so as to provide those of ordinaryskill in the art with a complete disclosure and description of how thecompounds, compositions, articles, devices and/or methods claimed hereinare made and evaluated, and are intended to be purely exemplary and arenot intended to limit the disclosure. Efforts have been made to ensureaccuracy with respect to numbers (e.g., amounts, temperature, etc.), butsome errors and deviations should be accounted for. Unless indicatedotherwise, parts are parts by weight, temperature is in ° C. or is atambient temperature, and pressure is at or near atmospheric.

1. Example 1 Biosensor-Based Cell Toxicity Screening

Profiling compounds by virtue of their cytotoxic and anti-proliferativeeffects is often used to profile potential anticancer agents. One suchphenotype is the compromise in plasma membrane integrity when cells areexposed to cytotoxic agents, including dimethyl sulfoxide (DMSO). Usinga waveguide-based biosensor technique, the feasibility for monitoringthe effect of DMSO on both Chinese hamster ovary (CHO) and A431 cellswas examined. Approximately 10×10⁵ cells were placed into each well of aCorning Epic LID microplate. These cells were cultured in serum mediumfor overnight to ensure that the cells became adherent to the substratesurface and reach at least 80% confluence. The response of cells to DMSOat different concentrations (1%, 2%, 5%, 10%, 15%, 18% and 20%) wasexamined. Higher concentrations of ˜≧25% of DMSO result in bulk indexchanges which are beyond the maximum dynamic range of the sensor usedand the signal was lost. At lease two sets of experiments were carriedout for each cell line.

a) Materials and Methods

All cell lines were purchased from American Type Cell Culture. DMSO wasobtained from Sigma Chemical Co. (St. Louis, Mo.). The Live/DEAD cellviability reagent kit for animal cells was obtained from MolecularProbes (Eugene, Oreg.).

Both A431 and CHO-K1 cells were grown in Dulbecco's modified Eagle'smedium (DMEM) supplemented with 10% fetal calf serum, 100 μg/mlpenicillin, and 100 μg/ml streptomycin. For cell culture, ˜10×10⁵ cells,either A431 or CHO-K1, were suspended in 200 μl medium were placed ineach well of a 96 well Corning Epic Biosensor microplate, and werecultured at 37° C. in air/5% CO₂ for overnight. Before the assays, thecells were washed once with the corresponding medium. During the assays,the cells in 100 μl medium were subject to two 25 μl HBSS buffersolutions containing 20 mM HEPES, pH 7.4, each separated by at least 15minutes before 50 μl DMSO solution was applied. During all these steps,a parallel angular interrogation system was used to monitor the realtime kinetics of cellular responses.

After assays, the corresponding resulting cells were immediately subjectto Live/DEAD staining using the protocol recommended by the supplier.After staining, fluorescence microscopy (a Zeiss Axioplan fluorescencemicroscope) was used to visualize the morphology and fluorescencedistribution of treated and untreated cells.

b) Results

Results showed that cells that had adhered to the biosensor gave rise toa similar response curve. As shown in FIG. 29, the DMSO-induceddose-response and time-dependent response curve of a CHO cell layerindicates that at a DMSO concentration of <20%, the response is almostfeatureless, except that there is a gradual decrease after introductionof DMSO solution. It is noted that there is an initial and rapidincreased phase, which is due to bulk index change right after the DMSOat all concentrations was introduced. However, when the concentration ofDMSO reaches 20%, there are four events that can be observed: (A) agreat response signal due to the bulk index change right after theintroduction of DMSO solution; (B) a small decreased signal, probablydue to the mixing of two fluids in the well; (C) a slow and steadyincreased signal probably because DMSO at those concentrationspenetrates and replaces the biofluid inside the cells; and (D) aprolonged and decreased signal due to the loss of proteins or otherbiological molecules of cells caused by the toxicity of highconcentrations of DMSO and the resulting lost integrity of the cellsurface membranes. It is known that the refractive index values are:1.3328 for the aqueous buffer medium used in this study 1.437 for DMSO,and 1.5 for proteins. In addition, there is about 70% (weight) forbiofluid, which consist primarily of water with a refractive index of1.3328, inside cells. Another 30% includes proteins, DNA, RNA, lipidmolecules. It is also known that when the concentration of DMSO is lowerthan 10%, cell membranes are not significantly affected by DMSO duringthe duration of experiments; however, when the concentration of DMSO isbetween 10% and 20%, there is increasing percentage of cell membraneswhich are compromised. At higher concentration, nearly all cellmembranes have been compromised (Beske, O., et al., “A novel encodedparticle technology that enables simultaneous interrogation of multiplecell types”, J. Biomol. Screening. 2004, 9, 173-185).

Similar dose response curves have been observed for DMSO acting on A431cells (FIG. 30). The different behavior for the event B between CHOcells and A431 cell lines is likely due to the different attachment andmorphology of the two types of cells on the substrate. CHO cells tend tospread much less than A431 cells, resulting in a thinner layer of A431cells attached on the substrates, which means that the biofluid exchangeevent (Event C) should be less pronounced than the biologicalredistribution event, when the lost of materials from effected cellsthat account for most of the event D are similar to both cell lines.

2. Example 2 HT Screening Compound Toxicity with Optical Sensor

a) Methods for High Throughput Screening Compound Toxicity

One aspect according to the present invention is to provide methods thatare suitable for high throughput screening compound toxicity andapoptosis using label free optical-sensors. The present methods allowone to detect, compound toxicity within a couple of seconds for a wholeplate.

The principal of the present methods lies in the fact that toxicity of agiven compound could lead to cell leakage, and even death. This, inturn, results in the inhomogeneity of the sensor surface wherein thecells are cultured. During the toxicity studies, the biosensors sensethree types of area: area having viable cell, area having dead or dyingcells (in which the dead cells tend to loss their intracellularcomponents, leading to the altered refractive index), and no-cell area.The inhomogeneity formation could cause changes in the PWHM of theresonant peak of a given guided mode or the width and distribution ofthe resonant band image, which all are dependent on the cell density. Inspecial cases wherein the cells cultured on the film surface areoriented or have certain type of preferred structure, or wherein thecells at certain areas are sensitive to toxic compounds, the compoundtoxicity could lead to the occurring of fine structures such asshoulders (which lead to resonant peak and band broadening) and evensplitting of resonance peaks.

Considering that the cells are pre-cultured on waveguide sensor platesand reach high confluency (>75%), the sensors sense mostly the livecells with a refractive index of ˜1.37, as well as the cover medium witha refractive index of ˜1.33. The PWHM of the TM₀ peak is relatively low.After a toxic compound is added, the cells start to be affected. Theaffected cells undergo both physical and physiological changes (i.e.,morphology, shape, and intracellular component rearrangement).Ultimately the affected cells die. At certain time after compoundtreatment, there are mixed populations of cells: live cells, affectedcells and dead cells. Therefore, as the time increases after compoundtreatment, the PWHM of the TM₀ peak starts to increase from itsrelatively low level, reach its maximum at certain time, and start itsdecay to original low level again with a decreased overall response(i.e., angular or wavelength shift). The kinetics to reach its maximumis dependent on cell line and mechanism of the compounds acting on thecells. This process is inverse to the cell attachment and spreadingprocesses.

In one embodiment, the present invention provides a method for highthroughput screening compound toxicity on cells using opticalbiosensors, which comprises of: (a) Provide a microplate that there isan optical-based label free biosensor embedded in the bottom of eachwell; (b) Place cells into each well to cover the biosensor such thatthe cells attach and reach high confluency onto the surface of thebiosensor; (c) Apply a compound solution into the cell medium of eachwell; (e) Collect optical waveguide lightmode spectra at certain time.Comparing the PWHM of each compound with a control well wherein thecells are not exposed to any compound solution, the toxicity ofcompounds can be evaluated using the single data point. If necessary,time-dependent PWHM changes can be also recorded to study the kinetics.

In another embodiment, the present invention provides alternativemethods to evaluate compound toxicity, which comprises of: (a) Provide amicroplate that there is an optical-based label free biosensor embeddedin the bottom of each well; (b) Place cells into each well to cover thebiosensor such that the cells attach and reach desired confluency ontothe surface of the biosensor; (c) Apply a compound solution into thecell medium of each well; (e) Collect images of TM₀ mode resonanceangular band of the whole sensor area of each well at certain time.Comparing the widths of the resonant bands of sensors that have beentreated with a compound solution with that of a control well wherein thecells are not exposed to any compound solution; the toxicity ofcompounds can be evaluated.

Profiling compounds by virtue of their cytotoxic and anti-proliferativeeffects is often used to profile potential anticancer agents. One suchphenotype is the compromise in plasma membrane integrity when cells areexposed to cytotoxic agents, including dimethyl sulfoxide (DMSO). Usinga waveguide-based biosensor technique, the feasibility for monitoringthe effect of DMSO on both Chinese hamster ovary (CHO) and A431 cellswas examined using the high throughput methods.

FIG. 31A shows the intensity of the incoupled light as a function of theincident angle for a layer of CHO cells with different confluencies(30%, 50% and 90%) cultured on Nb₂O₅-based optical waveguide biosensors.The coupling mode is transverse magnetic (TM₀) mode. FIG. 31B shows thewidth of the peak at half-maximum (PWHM) of the TM₀ mode is calculatedand plotted as a function of CHO cell confluency. As the confluency ofcells increases, the PWHM increases, reaches at maximum at around 50%confluency, and starts decrease to starting value. It is worthy notingthat there is small shoulder peak for the incoupled peak for cells atall confluency level, but not for the sensors that have no cellsattached. This is probably due to the fact that CHO cells prefer toattach onto the grating sensor surfaces with preferred orientation (seeFIG. 35A).

FIG. 32 shows the TM₀ mode resonant peak of a layer of CHO cells withtwo different confluencies, 5% (Left) and 75% (right), respectively,cultured on a waveguide grating sensor. The resonant peak spectra wererecorded at different times after addition of DMSO (with a finalconcentration of 18%). For cell density below ˜25%, there is no changein the PWHM value over time. However, when the confluency of cells onsensors is high (>70%), there is an initial increase in PWHM followed bydecreasing PWHM value. Besides the broadening of resonance peak, thereis the occurrence of fine structure such as shoulders and even splittingof the resonance peak at the time of ˜25 min after DMSO treatment.Interestingly, the broadening or shape changes of the resonant peaks inresponse to DMSO treatment is a dynamic process, suggesting that theDMSO-induced cell responses are consistent with certain cellularsignaling pathways, such as apoptosis.

FIG. 33 shows the TM₀ mode resonance band images of the whole sensorscovered by a layer of CHO cells at different confluencies. The imagesare taken after 25 min treatment with buffer (column 2), and with 18%DMSO (column 1). The images suggest that (i) the cells treated withbuffer solution do not result in any changes in the resonance band ofthe whole sensors no matter what the confluency of the cells is; and(ii) the cells treated with 18% DMSO give rise to the confluencydependent resonance band broadening. When the confluency of cells isabove 70%, there is DMSO-induced resonance band broadening. Theseresults suggest that the broadening of the resonance band broadening canbe used as a signature for compound toxicity; and cell density orconfluency is important in order to make this type of evaluation valid.Similar to the resonant peak spectra, the broadening or shape changes ofthe resonant band images in response to DMSO treatment is a dynamicprocess, suggesting that the DMSO-induced cell responses might berelated to certain cellular signaling pathways, such as apoptosis. Moreimportantly, the resonant band images for all 96 sensors within amicroplate can be collected within 3 seconds, suggesting that thepresent method based on resonant band images or spectra offers anultra-high throughput technique for cell toxicity evaluation andcompound toxicity screening.

FIG. 34 shows the TM₀ mode resonance band images of the whole sensorscovered by a layer of CHO cells at same confluency (˜95%). The imagesare taken after 25 min treatment with buffer (6 wells in column 2), andwith different concentrations of DMSO (6 wells in column 1, and 6 wellsin column 3, as indicated in the FIG. 34). The results show that thetoxicity effect of DMSO is dependent on the concentration; only higherconcentrations cause significant cell toxicity, as indicated by thechanges in band shape. A particularly interesting finding is that whenthe concentration of DMSO used is ˜15%, there is a second resonance bandappearing, probably due to the preferred orientation of CHO cellscultures on the sensors. The CHO cells seem align with the gratingstructure under culture conditions (see FIG. 35). These results werefound to be consistent with and thus confirmed by conventional Live/DEADcell staining methods (data not shown).

3. Example 3 High Throughput Proliferation Assays

FIG. 36A shows the intensity of the incoupled light as a function of theincident angle for CHO cells cultured onto waveguide grating sensorsurfaces when three different seeding numbers of cells are used forculture under normal growth condition for 36 hours. The coupling mode istransverse magnetic (TM₀) mode. FIG. 36B shows the width of the peak athalf-maximum (PWHM) using TM₀ mode is calculated and plotted as afunction of initial seeding cell numbers. As the initial seeding numberof cells increases, the PWHM increases, reaches at maximum at between20000 and 30000 initial seeding cells (the corresponding confluency isaround 50%), and starts decreasing to a starting value. It is worthynoting that there is an obvious shoulder peak for the incoupled peak forcells at all confluency levels, but not for the sensors that have nocells attached. Again, this is likely due to the fact that CHO cellsprefer to attach onto the grating sensor surfaces with preferredorientation (See FIG. 35). Interestingly, the results shown here areconsistent with those obtained using different seeding numbers of cellsto reach different cell densities after a fixed period of time (see FIG.31), suggesting that the present method is reproducible.

FIG. 37 shows the TM₀ mode resonance band images of the whole sensorscovered by CHO cells, after cultured on the waveguide grating sensorsfor 36 hours; different wells host different initial seeding numbers ofcells. The shape and position of the TM₀ mode resonance band images ofthe whole sensors is observed to be dependent on initial seeding cellnumbers, suggesting that the sensors are sensitive to cell density; theproliferation rate of CHO cells depends on initial seeding cell numbers,as confirmed by cell density analysis using fluorescence microscopyafter stained with Live/Dead cell kit from the Molecular Probes. Thecorresponding confluencies are 5%, 30%, 55%, 75% and 95% for the initialseeding number of 10000, 20000, 30000, 40000 and 50000 cells,respectively.

4. Example 4 Cell Signaling Pathway Studies Using Biosensors

a) Materials and Methods

All cell lines were purchased from American Type Cell Culture. Allchemicals were obtained from either Sigma Chemical Co. (St. Louis, Mo.),or Tocris Chemical Co. (St. Louis, Mo.).

Both A431 and CHO-K1 cells were grown in Dulbecco's modified Eagle'smedium (DMEM) supplemented with 10% fetal calf serum, 100 μg/mlpenicillin, and 100 μg/ml streptomycin. For cell culture, certainnumbers of cells (2×10⁵ to 1×10⁶), either A431 or CHO-K1, were suspendedin 200 ml medium were placed in each well of a 96 well Corning EpicBiosensor microplate, and were cultured at 37° C. in air/5% CO2 forcertain time until the cell density reached 90% and above (unlessspecified). The resulted cells were termed as “profilerating” cells. The“quiescent” cells were obtained by culturing the proliferating cells ofdesired confluencies with a medium containing no or little (˜0.1% fetalbovine serum (FBS)) for at least 16 hours.

The cells, either proliferating or quiescent cells, were either directlyused for assays or washed once with the corresponding medium (bothresult in no obvious difference in cell responses). During the assays,the cells in 100 μl medium were subject to two 25 μl HBSS buffercontaining 20 mM HEPES, pH 7.4, each separated by at least 15 minutesbefore 50 μl stimulus-containing solution was applied. During all thesesteps, a parallel angular interrogation system was used to monitor thereal time kinetics of cellular responses. For compound effect studies, amodified protocol was used which starts with 50 μl medium, and subjectto sequential treatment: 25 μl HBSS buffer twice (each separated by atleast 15 minutes), 50 μl compound solution and finally 50 μlstimulus-containing solution.

The sensors used were 96 well Corning Epic biosensor microplates (asshown in FIG. 1 and FIG. 2 a), and used directly for cell culture. Thedetection system used can be that of U.S. patent application Ser. No.10/602,304, filed Jun. 24, 2003 having publication no. US-2004-0263841,published Dec. 30, 2004 and U.S. patent application Ser. No. 11/019,439,filed Dec. 21, 2004, and U.S. patent App. For “OPTICAL INTERROGATIONSYSTEM AND METHOD FOR 2-D SENSOR ARRAYS” by N. Fontaine, et al., filedon Mar. 31, 2005, all of which are herein incorporated in theirentireties by reference but at least for biosensors and their uses.

b) Results

(1) Real Time Monitoring the Ligand Binding and Sequential SignalingEvents of RTKs

FIG. 6A shows a time-dependent response of a layer of quiescent orstarved A431 cells (monitored using optical biosensor) before and afteraddition of 8 nM EGF. The A431 cell line is a cancer cell line havingendogenously over-expressed EGFRs. A431 cells in a Dulbecco's modifiedEagle's medium (DMEM) medium containing 10% fetal calf serum (FCS) wereapplied to each well of a microplate which has a waveguide biosensor inthe bottom of each well. The cells were cultured overnight at 37° C.,the serum medium was exchanged with a medium containing only 0.1% serum,and the cells were continuously cultured for another 18 hours. The wholetime course was obtained at room temperature (˜20° C.). After additionof EGF (A), EGF-treatment of quiescent A431 cells, obtained by beingcultured in 0.1% fetal bovine serum (FBS) for 18 hours, gave rise to atime-dependent response that consists of three distinct, sequentialphases: (i) a positive phase with increased signal (P-DMR) (Point C to Din FIG. 6A), (ii) a net-zero phase (Point D to E), and (iii) a decayphase with a decreased signal (N-DMR) (Point E to F to G). It was notedthat there is a rapid response change in signal, lasting for less than20 sec (Point B to C in FIG. 6A), which occurs upon the introduction ofa 50 ml EGF solution into the well. This rapid change is due primarilyto a bulk index change, which temporarily overwhelms any DMR signal. Themeasured P-DMR signal is mainly due to the recruitment of intracellularcomponents to activated EGFRs and the flatness of the cells due to theinvagination of plasma membranes after EGFR activation, whereas celldetachment and receptor internalization are two major contributors tothe N-DMR event. However, the P-DMR event might also involve non-cellfunction-related events, including solution diffusion and temperaturedifferences between the cell medium and the compound solution.

The kinetics of the above-mentioned steps in the response curve isconsistent with that of ligand binding, phosphorylation and traffickingevents of EGF-induced EGFR signaling reported in the literature (B.Schoeberl, C. Eichler-Jonsson, E. D. Gilles, G. Muller, “ComputationalModeling of the Dynamics of the MAP Kinase Cascade Activated by Surfaceand Internalized EGF Receptors,” Nat. Biotech. 20, 370 (2002).Biological and biochemical studies have shown that at 37° C., EGF-boundreceptors can be internalized into early endosomes within ˜5-20 minwhich locate at nearly the inner face of cell membranes. Afterwards,these EGFRs in complexation with other components are transferred tolate endosomes (20-60 min) and lysosomes (>60 min) for degradation ofwhich both are located relatively far away from the inner face of thecell membranes (i.e., during the trafficking, these receptors move awayfrom the sensor surface). There is a continual flux of receptors andligand through different compartments; and multiple steps dictate theiroverall dynamic distribution. EGF-bound receptors only spend arelatively short time at the cell surface (˜3 min) owing to rapidinternalization.

(2) Methods to Measure the Expression Level and Cell-Surface ExpressionLevel of EGFR

The A431 cell, endogenously over-expressing epidermal growth factorreceptors (EGFRs) (˜1,700,000 copies per cell), is a well-studied modelfor EGFR signaling (A. Glading, P. Chang, D. A. Lauffenburger, and A.Wells, “Epidermal growth factor receptor activation of calpain isrequired for fibroblast motility and occurs via an ERK/MAP kinasesignaling pathway,” J. Biol. Chem. 2000, 275:2390-2398). Stimulation ofquiescent A431 cells with EGF at room temperature or 37° C. ultimatelyleads to receptor endocytosis, refractile morphological changes and celldetachment from the extracellular matrices (Z. Lu, G. Jiang, P.Blume-Jensen, and T. Hunter, “Epidermal growth factor-induced tumor cellinvasion and metastasis initiated by dephosphorylation anddownregulation of focal adhesion kinase,” Mol. Cell. Biol. 2001, 21,4016-4031). Thus, EGF stimulation results in significant massredistribution within the A431 cells, as measured in real time using thearrayed interrogation system (see FIG. 6A, FIG. 18). Results showed thatEGF-induced DMR responses of A431 cells strongly depend on the culturecondition. EGF-treatment of A431 cells cultured in 0.1% FBS for 20 hoursgave rise to a time-dependent response that consists of three distinct,sequential phases: (i) a positive phase with increased signal (P-DMR)(Point C to D in FIG. 6A), (ii) a net-zero phase (Point D to E), and(iii) a decay phase with a decreased signal (N-DMR) (Point E to F).However, A431 cells treated with 0.1% FBS for only 4 hours gave rise tosimilar response but with altered kinetics and much smaller amplitudes,compared to the quiescent A431 cells. Conversely, proliferating A431cells (cultured with 10% FBS) only gave rise to a P-DMR event inresponse to EGF stimulation. Furthermore, no significant responses wereobserved for either quiescent or proliferating Chinese hamster ovary(CHO) cells, consistent with the fact that CHO cells do not endogenouslyexpress EGFR (E. Livneh, R. Prywes, O. Kashle, N. Reiss, I. Sasson, Y.Mory, A. Ullrich, and J. Schlessinger, “Reconstitution of humanepidermal growth factor receptors and its deletion mutants in culturedhamster cells,” J. Biol. Chem. 1986, 261, 12490-12497.). These resultssuggested that the EGF-induced DMR signals are EGFR dependent.

FIG. 39 summarizes the P-DMR and N-DMR signals for these three types ofcells. The results show that there is no clear P-DMR nor B-DMR signalwhen CHO cells were incubated with EGF, consistent with the fact thatCHO cells do not express EGFR. In contrast, the P-DMR and N-DMR signalsinduced by EGF stimulation are 3.08, and 2.34, respectively, forquiescent A431 cells. However un-starved (i.e., proliferating) A431cells gave rise to much smaller P-DMR signals with no obvious N-DMR.These results confirm the fact that serum growth medium affects the cellsurface expression level of EGFRs; higher serum medium results in lowercell surface EGFR expression due to the fact that the serum contains EGFand many other growth factors.

(3) Methods to Determine the Potency of Ligands to RTKs

As shown in FIG. 7, stimulations with EGF at different concentrationsall led to a similar response (FIG. 7A); however, three major parametersdefining the response displayed a clear tendency to the concentrationsof EGF used. The higher the EGF concentration is, (i) the greater arethe amplitudes of both the P-DMR and the N-DMR signals, (ii) the fasterare both the P-DMR and the N-DMR events, and (iii) the shorter is thetransition time τ from the P-DMR to the N-DMR event. The P-DMR eventinvolves cell function-related and other contributions. The possiblecontributors include, but are not limited to, cell flatness in responseto treatment, cell membrane invigination, recruitment of intracellularcomponents and cytoskeleton remodeling, and to less extent, EGF binding.Non-cell function-related events, including solution diffusion andtemperature differences between the cell medium and the compoundsolution, might also complicate the analysis. Because of those, we hadobserved a complicated relationship of the overall P-DMR amplitudes withthe EGF concentrations. When the amplitudes of the P-DMR events showed acomplicated relationship with the EGF concentrations, the amplitudes ofthe N-DMR signals were clearly saturable to EGF concentrations,resulting in an EC₅₀ of ˜1.45 nM (FIG. 7B). The transition time τ inseconds was found to decrease exponentially with the increasingconcentration C of EGF (FIG. 7C):

τ(C)=946*e ^(−0.144C)+1130

In addition, the decay of the N-DMR signal can be fitted with non-linearregression. The one-phase decay constant κ obtained was also saturable,resulting in a K_(d) of 5.76 nM (FIG. 7D). The results indicated that(i) the EGF-induced DMR signal is dependent on EGFR activation; (ii) theoptical biosensors can be used to determine the potency of the ligandsbased on the ligand-induced mass redistribution signals.

(4) Methods to Screen Modulators that Affect RTK Signaling at DifferentStages

FIG. 40 shows the effect of pre-treatment with different compounds onthe time-dependent response of 8 nM EGF-induced signaling for a layer ofstarved A431 cells. FIG. 41 summarizes the net changes of binding andDMR signals under different conditions. The results showed that cellpermeable dynamin inhibitory peptide (DIP) (Burke, P., et al.,“Regulation of epidermal growth factor receptor signaling by endocytosisand intracellular trafficking”, Mol. Biol. Cell. 2001, 12:1897-1910)totally blocks the N-DMR signal, but slightly increases the P-DMR signalwith much slower kinetics. DIP is a cell permeable inhibitor of theGTPase dynamin that competitively blocks binding of dynamin toamphiphysin, preventing endocytosis ((Burke, P., et al., “Regulation ofepidermal growth factor receptor signaling by endocytosis andintracellular trafficking”, Mol. Biol. Cell. 2001, 12: 1897-1910). Theseobservations suggest that the N-DMR signals involve receptortranslocation and its associated cell morphology changes, because theEGF-induced EGFR internalization occurs mainly through dynamin-dependentpathways and involves the cytoskeleton rearrangement, and the couplingof dynamin with activated EGFRs affects the affinity of EGF binding. Thetotal P-DMR signal in the presence of DIP is 50% more than that in theabsence of DIP; suggesting that during the P-DMR phase (from C to D inFIG. 6A) there are some activated EGFRs that have been internalized. Itis known that EGF-bound receptors only spend a relatively short time atthe cell surface (˜3 min) at 37° C. owing to rapid internalization. Inaddition, it has been estimated that during trafficking, 48.7% and96.2%, respectively, of the formed coated- and smooth-pit EE recycleback to the cell surface; i.e., receptor internalization throughclathrin-coated pits is sufficient to account for the majority ofendocytosis. Therefore, receptor internalization through the coated-pitEE vesicles is the dominant mechanism of receptor accumulation withincells, and this is particularly true when ligand is present in thesystem.

The pretreatment of starved A431 cells by wortmannin has no obviouseffect on both the P-DMR and N-DMR signals as well as their kinetics.Wortmannin is a potent, selective, cell permeable and irreversibleinhibitor of phosphatidylinositol 3-kinase (PI 3-kinase) with an IC₅₀ of2-4 nM (Powis, et al, “Wortmannin, a potent and selective inhibitor ofphosphatidylinositol-3-kinase”, (1994) Cancer Res. 54 2419). Thissuggests that the blocking of the PLC-gamma pathway does not affect bothevents of the cells in response to EGF stimulation.

The pretreatment of starved A431 cells with growth hormone (GH), PD98059and PP1 (also See FIG. 43) not only significantly reduced both thebinding and DMR signals, but also results in a decrease in the kineticsof both P-DMR and N-DMR events. PD 98059 is a specific inhibitor ofmitogen-activated protein kinase kinase (MAPKK/MEK) and acts by bindingto the inactivated form of MEK, thereby preventing its phosphorylationby cRAF or MEK kinase (IC₅₀=2-7 μM) (Alessi, et al., “PD 98059 is aspecific inhibitor of the activation of mitogen-activated protein kinasekinase in vitro and in vivo”, Nov. 17, 1995, J. Biol. Chem., Vol. 270,No. 46, pg. 27489-27494). The blocking of the MAPKKs by PD98059 possiblyreduces the magnitude of the signal, and the duration of the response ofthe cells having EGFR to EGF binding. PP1 is a potent inhibitor ofSrc-family tyrosine kinases, and inhibits p56lck and p59fynT (IC₅₀ of 5and 6 nM, respectively) and also moderately inhibits p38, CSK, PDGFreceptors, RET-derived oncoproteins, c-Kit and Bcr-Abl (Liu et al,Structural basis for selective inhibition of Src family kinases by PP1”,(1999) Chem. Biol. 6, 671). Epidermal growth factor (EGF) binding to itsreceptor causes rapid phosphorylation of the clathrin heavy chain attyrosine 1477, which lies in a domain controlling clathrin assembly.EGF-mediated clathrin phosphorylation is followed by clathrinredistribution to the cell periphery and is the product of downstreamactivation of SRC kinase by EGF receptor (EGFR) signaling. In cellslacking SRC kinase, or cells treated with a specific SRC family kinaseinhibitor, EGF stimulation of clathrin phosphorylation andredistribution does not occur, and EGF endocytosis is delayed. These areconsistent with the current observations.

Growth hormone (GH) is a four-helix bundle protein that sharesstructural similarity with a large class of hormones and cytokines,including prolactin and various interleukins and colony stimulatingfactors (Huang, Y., et al., “Growth hormone-induced phosphorylation ofepidermal growth factor (EGF) receptor in 3T3-F442A cells”, J. Biol.Chem. 278, 18902-18913). GH exerts its profound somatogenic andmetabolic regulatory effects by interacting with the GH receptor (GHR),a cell surface glycoprotein member of the cytokine receptor superfamily.Recent studies suggest that there is cross-talk between the GHR andmembers of the EGFR family, examples of seemingly disparate types ofsignaling receptors (a cytokine receptor and a family of tyrosine kinasereceptors, respectively). GH causes phosphorylation of epidermal growthfactor receptor (EGFR; ErbB-1) and its family member, ErbB-2. ThisGH-induced EGFR tyrosine phosphorylation was shown to require JAK2, butnot EGFR, kinase activity. GH causes a decrease in basal and EGF-inducedErbB-2 tyrosine kinase activation and tyrosine phosphorylation,suggesting that GH causes an ERK pathway-dependent phosphorylation ofErbB2 that renders it desensitized to activation in response to EGF.Fluorescence microscopy studies indicated that EGF-induced intracellularredistribution of an EGFR-cyan fluorescent protein chimera was markedlyreduced by GH co-treatment. This is also consistent with the currentobservations (Huang, Y., et al., “Growth hormone-induced phosphorylationof epidermal growth factor (EGF) receptor in 3T3-F442A cells”, J. Biol.Chem. 278, 18902-18913).

(5) Dose Dependent Suppression of the EGF-Induced Responses of QuiescentA431 Cells Induced by AG1478

FIG. 42 shows a dose dependent suppression of the EGF-induced responsesof quiescent A431 cells induced by AG1478. To confirm that these DMRevents are dependent on receptor phosphorylation, a potent and specificEGFR kinase inhibitor tyrphostin AG1478 was used. The A431 waspre-starved in a medium without any FBS for 20 hours, resulting insignificantly faster kinetics for the P-DMR event and shorter transitiontime than those starved in 0.1% FBS medium for the same period of time(FIG. 42A). The pretreatment of A431 cells with AG1478 at differentconcentrations for one hour resulted in a dose-dependent suppression ofthe EGF-induced response, yielding a typical inhibition curve with anIC₅₀ of ˜194 nM when the amplitude of the N-DMR signal was plotted asthe function of AG1478 (FIG. 42 a and b). However, pretreatment of A431with 0.5% dimethyl sulfoxide had a little effect on the EGF-inducedresponse (data not shown). These data indicate that EGFR kinasephosphorylation is required for the EGF-induced DMR changes; and the DMRsignals obtained using optical biosensors can be used to determine thepotency of modulators that play an important role in the DMR eventmeasured.

(6) The Effect of Ras/MAPK Pathway Modulators on 32 nM EGF-InducedResponse of the Quiescent A431 Cells

EGF regulates cell proliferation and differentiation, and uses, at leastin part, mitogen-activated protein kinases as downstream signals.Furthermore, ERK activation seems to represent a global, negative signaldownstream of EGFR activation, which may be important in deadhesion.Thus, the effect of inhibitors targeting Ras-MAPK pathways, includingMEK inhibitors U0126, p38 MAPK inhibitor SB203580 and SB20219, and a JNKinhibitor SP600125, were examined (see FIG. 44). U0126 significantlycompressed the amplitudes of both the P-DMR and N-DMR signals with adelayed time τ. This suggests that inhibition of MEK1/2 prevents celldetachment and movement that leads to the N-DMR signals, consistent withprevious studies. However, the endocytosis of activated EGFR could stilloccur when the MEK1/2 were inhibited. Since the endocytosis occurs awayfrom the sensor surface compared to the cell detachment and movement,the endocytosis should contribute significantly less to the overallresponse. Therefore, the EGF-induced responses of those quiescent A431pretreated with MEK1/2 inhibitor is consistent with receptorendocytosis. This was further supported by the kinetics of the responseswhich are consistent with computational modeling results. In contrast,both SB203580 and SB20219 only led to a partial attenuation, whereasSP600125 had little effect on the EGF-induced response. These resultsindicate that in quiescent A431 cells EGF simulation of the DMRresponses involve the Raf-MEK pathway, and proceeds through MEK.

(7) The Effect of Protein Kinase Inhibitors on 32 nM EGF-InducedResponse of the Quiescent A431 Cells

The effect of protein kinase inhibitors on the EGF-induced response wasexamined since EGFR signaling involves a variety of other proteinkinases. Pretreatment of A431 with 1 μM wortmannin (a potent andselective PI3K inhibitor), 1 μM KT 5720 (a potent and selectiveinhibitor of protein kinase A), 10 μM KT5823 (a selective inhibitor ofprotein kinase G), and 10 μM KN 62 (a selective inhibitor of CaM kinaseII) had little effect on the response. In contrast, GF 109203 (aselective inhibitor of protein kinase C) exhibited partial attenuationon the response (see FIG. 45). These results indicate that proteinkinase C, but not PI3K, protein kinase A and CaM II, alters the abilityof EGF to stimulate the DMR changes.

(8) The Effect of Cytoskeleton Modulators on 32 nM EGF-Induced Responseof the Quiescent A431 Cells.

Since the trafficking of targets and morphological changes of cells inresponse to EGF stimulation requires the re-modeling of cytoskeletonstructure, the effect of cytoskeleton modulators on the EGF-induced DMRresponse was examined (see FIG. 46). Pretreatment of A431 with actinfilament disruption agents, either cytochalasin B or latrunculin A,totally abolished the N-DMR signal, and resulted in the prolonged P-DMRphase with significantly slow kinetics. The two toxins perturb actinassembly and disassembly by distinct mechanisms: cytochalasin B capsactin filaments and ultimately leads to actin filament disassembly,while latruculin A sequesters actin monomers and causes actin filamentdisassembly. However, neither a stabilizing polymeric F-actin agentphalloidin or microtubule disrupters vinblastine and nocodazole (datanot shown), had hardly any effect on the EGF-induced response. Theseresults confirm that the movement of cells resulting in the N-DMR signalis not due to reorganization of preexisting actin but, rather, actinpolymerization, and is independent of microtubule assembly. In contrast,since the trafficking of intracellular proteins requires actinfilaments, the P-DMR signal is at least partially due to the recruitmentof intracellular components to the activated receptors. Extra evidencecame from the effect of the cell membrane permeable dynamin inhibitorypeptide (DIPC). Pretreatment of A431 with DIPC at 50 μM gave rise tosimilar response to those pretreated with cytochalasin B and latrunculinA, but with faster kinetics.

(9) The Effect of Phosphodiesterase Inhibitors on 32 nM EGF-InducedResponse of the Quiescent A431 Cells

Cyclic AMP (cAMP) has served as a paradigm of an intracellular secondmessenger, and regulates a myriad of cellular functions, such asmetabolism, contractility, motility, and transcription in virtually allcell types. Previous studies showed that cAMP pathways crosstalk withand attenuate growth factor-stimulated MAP kinase activity that dependson the cellular context. Since phosphodiesterases (PDE) regulate thecAMP levels in cells, the role of PDEs on the EGF-induced response wasstudied using PDE inhibitors cilostamide, milrinone, Ro 20-1724,R(−)-rolipram and Zardaverine (each at 10 μM). None of these inhibitorshad an obvious effect on the responses (see FIG. 47), suggesting thatcAMP is not involved in the overall DMR response. Previous studies haveshown that protein kinase A can antagonize the activity of Raf-1 andthus regulate Ras-MAPK pathway through modulating PDE activities.However, in quiescent cells Raf-1 exhibits a constitutivephosphorylation which is not sensitive to a PKA inhibitor, consistentwith our observations that a PKA inhibitor KT5720 (FIG. 45) and PDE4inhibitors Ro 20-1724 and R-(−)-rolipram had little effect on theEGF-induced DMR signals.

(10) EGF Induced EGFR Internalization, Cell Morphology Changes, andDirectional Mass Redistribution in A431 Cells at Room Temperature (22°C.)

Stimulation of A431 cells with EGF at room temperature triggers EGFRactivation through receptor dimerization and sequent autophosphorylationthat ultimately leads to receptor endocytosis (see FIG. 48A-C,refractile morphological changes (see FIG. 48D), and directional massredistribution (see FIG. 2A, FIG. 18 and others). By selectivelyremoving the surface-bound tetramethylrhodimine-labeled EGF (TMR-EGF)using acid stripping method, the extent of EGFR internalization wasexamined and found to be dependent on cell culture condition. Muchhigher cell surface and internalized receptors were found in quiescentcells than those in proliferating cells. The EGF-induced morphologicalchanges of quiescent cells were visualized by Texas red-phalloidinstaining after fixation. Previous studies showed that the A431 at 37° C.exhibits time-dependent refractile morphological changes and detachmentfrom the extracellular matrix upon EGF treatment. Consistent with thesestudies, actin remodeling started to change after ˜15 minutes of EGFtreatment, and this change became more dramatic at longer stimulation,as indicated by the rim of filamentous actin at the edge of the cell.

(11) Schematic Drawing Shows One Possible Mechanism for EGF-Induced DMRSignals-Receptor Endocytosis

Potential roles for the actin cytoskeleton in endocytosis. The model inFIG. 49 depicts how the cortical actin cytoskeleton can be involved indifferent steps of the endocytic process implicating potentialfunctional roles for molecules at the interface of endocytosis andcytoskeletal organization. Following the receptor activation by itscognate ligand (e.g., EGF), there are three major steps in receptorendocytosis: 1) spatial organization of the endocytic machinery.Cytoskeletal structures may organize or constrain the lateral mobilityof the machinery for endocytosis. Deformation and invagination of theplasma membrane may be supported by the cytoskeleton. 2) The corticalactin barrier underlying the plasma membrane might need to be dissolved.Actin polymerization may provide force to drive membrane fission duringendocytic vesicle formation., and 3) Actin polymerization may promotethe movement of newly formed endocytic vesicles into the cytoplasm byforming a comet tail.

5. Example 5 Method to Screening Modulators for Cytoskeleton

The pore-forming regents include detergents such as saponin and filipin,or toxin such as digitonin or streptolysin O. It is well known thattreatment of the cells with these reagents can result in the poreformation in cell surface membrane; the resulted permeabilized cells canrelease a certain amount of intracellular material, mainly solubleproteins. However, there are a great number of bio-materials that stillstay with these permeabilized cells due to the sequestration by directlybinding or association with the cytoskeleton structure. As a matter offact, these permeabilized cells retain many of the biological functionsof living cells such as protein synthesis. Treatment of the cells with acompound that can disrupt the cytoskeleton structure can result inreleasing significantly more bio-materials from these permeabilizedcells.

Cytoskeleton is a complex and dynamic network of protein filaments thatextends throughout the cytoplasm of eukaryotic cells. Cytoskeleton isinvolved in executing diverse activities in cells. It maintains cellshape by providing tensile strength for the cells. It also enables somecell motion (using structures such as flagella and cilia), and playsimportant roles in both intra-cellular transport (the movement ofvesicles and organelles, for example) and cellular division. Thecytoskeleton is involved in intracellular signaling and trafficking byproviding the “track” on which cells can move organelles, chromosomesand other things.

FIG. 50 presents the dose-dependent responses of CHO cells adherent onthe surface of a LID sensor in response to saponin as a function oftime. After the addition of saponin at different concentrations, adifferent response is evident. At low concentration, there is almost noresponse. When the concentration of saponin is above ˜20 ug/ml, there isa decreased signal followed by an increased response. The initialincreased signal can be most likely due to the flattening out of thecells on the surface of the sensor, resulting in a mass increase withinthe sensing volume of the sensor; whereas the decreased signal mostlikely reflects the loss of bio-materials from the cells; anotherpossibility is due to the rearrangement of cellular components and/ormorphology changes that lead to a net-decreased mass within the sensingvolume of the sensor. At the highest concentration tested, there is noinitial increased signal; conversely there is only a decreased signalwith significant greater response than those at lower concentrations.

The permeability of the cells treated with higher concentration ofsaponin can be evidenced by the fluorescence images of CHO cells stainedwith Texas Red-phalloidin after treated with different concentrations ofsaponin (data not shown). Texas Red-X phalloidin is a high-affinityprobe for F-actin that is made from a mushroom toxin conjugated.Staining using Texas Red-phalloidin requires that cells are permeable,generally done after formaldehyde-fixation. This is because thefluorescent phalloidin conjugates are not permanent to most live cells,although unlabeled phalloidin can penetrate the membranes of cells. Thestrong fluorescence inside the cells treated with high concentrations ofsaponin indicates the pore formation and the cells are permeable. Basedon this study, the concentration of saponin at 67 ug/ml was chosen forcompound screening.

FIG. 51 shows the saponin-induced and time-dependent responses of CHOcells after being pre-treated with different compounds. Results showthat these compounds can be mainly classified into four categories: (i)compounds (e.g., cytochalasin B) that cause increased loss ofbiomaterials, as evidenced by increased kinetics and amplitudes of theN-DMR signal; (ii) compounds (e.g., dynamin inhibitory peptide,brefeldin A) that show no effect on a saponin-induced response; (iii)compounds (e.g., phalloidin) that delay the loss of biomaterials insaponin-treated cells, but with similar total changes after longer time;and (iv) compounds (e.g., vinblastine) that block the saponin-inducedloss of biomaterials from the cells. These observations are consistentwith the known properties of these compounds. Cytochalasin B caps actinfilaments preventing assembly and, owing to the dynamic nature of actinfilaments, ultimately leads to actin filament disassembly. In contrast,phalloidin binds to F-actin and promotes actin polymerization.Vinblastine inhibits microtubule assembly by binding tubulin and inducesself association in spiral aggregates. Dynamin inhibitory peptide (DIPC)and brefeldin A are non-binders to actin or other filaments. Theseresults also suggest that actin filaments, but not other filaments,provide the most of sequestered sites for bio-macromolecules.

Staining with Texas Red-phalloidin after saponin-treatment reveals thatcytochalasin B-pretreated cells give rise to similar staining patterncompared to those pretreated with other compounds (data not shown). Thiscan be due to limited fluorescence resolution available. However,phalloidin-pretreated cells give rise to significantly lower staining.This is because the unlabeled phalloidin blocks F-actin staining bylabeled phallotoxins.

6. Example 6 Systems and Methods for Performing G Protein CoupledReceptor (GPCR) Cell Assays Using Label Free Optical Biosensors

FIGS. 52-60 provide various graphs and charts indicating the results ofseveral different experiments that were conducted to show that theoptical LID system can be used to monitor mass redistributions, such asGPCR translocations, within living cells. These translocations can belocated on a surface of an optical LID biosensor as disclosed herein.The particular data shown in FIGS. 52-60 was obtained using an opticalwaveguide grating sensor system and LID microplates (Nb₂O₅ plates),manufactured by Corning Incorporated. FIG. 52 is a graph that showsseveral agonist-induced responses within chinese hamster ovary cells 108(CHO 1008) that were monitored by the optical LID system 1000. It isknown that CHO cells 1008 endogenously express beta adrenergicreceptors, alpha2-adrenergic receptors, P2Y receptors, as well asbeta-arrestin and GRKs. It is also known that muscarinic receptors areendogenously expressed at very low level in the CHO cells 1008. In thisexperiment, approximately ˜5×10⁴ CHO cells 1008 were placed within eachwell of a microplate that contained an array of optical LID biosensors1004. The CHO cells 1008 were then cultured in 150 μl serum medium for24 hours to ensure that the CHO cells 1008 became adherent to thesubstrate surface 1010. The graph shows the optical responses of the CHOcells to four different compounds which were examined: (1) ATP (100 μM),agonist for P2Y receptors; (2) clonidine (10 μM), agonist foralpha2-adrenergic receptors; (3) epinephrine (100 μM), agonist for betaadrenergic receptors; and (4) oxotremorine M (10 μM), agonist formuscarinic receptors. Since muscarinic receptors are endogenouslyexpressed at very low level in CHO cells, oxotremorine M, agonist formuscarinic receptors, served as a control. Each of these agonists wasdirectly applied to a different one of the wells which contained theserum medium. The optical responses were then collected by the opticalLID system.

The results showed that these adherent CHO cells gave rise to similarkinetics and transitions as shown by the optical responses after theintroduction of the three agonists: ATP, clonidine, and epinephrine.Oxotremorine M caused almost no cell response. In FIG. 53, a kineticsanalysis of the later stage of the process revealed that all threeagonists (ATP, epinephrine, clonidine) resulted in a similar slowprocess. The changes for the Stage 3 as shown in FIG. 16, caused bythose agonists, are shown in the graph in FIG. 54. The similar changesmight reflect the fact that beta-arrestin, a critical component for GPCRtranslocation, could be the limiting factor in the CHO cells, given thatthe size of clathrin-coated pits and beta-arrestin are similar. FIG. 55is a graph that shows the results from an experiment which indicates theligand- and time-dependent response of a monolayer of living CHO cellson wave-guide biosensors. The agonists which were used included: (1)clonidine; (2) oxotremorine M; (3) NECA; and telenzepine, an antagonistfor M1 receptor, is also used.

FIG. 56 is a graph that shows the results from an experiment whichindicates the ligand- and time-dependent response of monolayer of livingCHO cells 108 with stably overexpressed rat muscarinic receptor subtype1 (M1) on wave-guide biosensors 104. The agonists which were usedincluded: (1) clonidine; (2) oxotremorine M; and (3) NECA; andtelenzepine, an antagonist for M1 receptor, is also used. FIG. 57 is agraph that shows the results from an experiment which indicates theligand-induced total change in response of monolayer of living CHO cellswithout (CHO) and with stably overexpressed rat muscarinic receptorsubtype 1 (M1CHO) on wave-guide biosensors 104. Results shown in FIGS.52 and 54-56 indicated that (1) there are alpha2 adrenergic receptorsexpressed in both CHO and M1-CHO cells; and their agonist (clonidine)induced mass redistribution signals; (2) there is relatively low oralmost no M1 receptor expressed in CHO cells, but high in M1-CHO cellssince its agonist (oxotremorine M) but not its antagonist (telenzepine)results in significantly larger responses in M1-CHO cells.

FIG. 58 is a graph that shows the results from an experiment whichindicates the effect of pre-incubation of a dynamin phosphorylationinhibitor (dynamin inhibitory peptide, DIP) on oxotremorine M-inducedtime-dependent response of a monolayer of living CHO cells without andwith stably overexpressed rat muscarinic receptor subtype 1 (M1CHO) onwave-guide biosensors. Results show that the pre-incubation of cellswith DIP almost totally eliminates the oxotremorine M-induced massdistribution responses in both cell lines, suggesting that oxotremorineM-induced mass distribution is dynamin-dependent. The dynamin-dependencyis common for most of agonist-induced GPCR translocation.

FIG. 59 is a graph that shows the results from an experiment whichindicates the effect of pre-incubation of a dynamin phosphorylationinhibitor (dynamin inhibitory peptide, DIP) on clonidine-inducedtime-dependent response of a monolayer of living Chinese Hamster Ovary(CHO) cells without and with stably overexpressed rat muscarinicreceptor subtype 1 (M1CHO) on wave-guide biosensors. Results show thatthe pre-incubation of both cell lines with DIP almost totally eliminatesthe clonidine-induced mass distribution response, suggesting thatclonidine-induced mass distribution is also dynamin-dependent.

FIG. 60 is a graph that shows the results from an experiment whichindicates the effect of pre-incubation of a dynamin phosphorylationinhibitor (dynamin inhibitory peptide, DIP) on NECA-inducedtime-dependent response of a monolayer of living CHO cells 108 withoutand with stably overexpressed rat muscarinic receptor subtype 1 (M1CHO)on wave-guide biosensors 104. Results showed that the pre-incubation ofboth cells with DIP has little effect on NECA-induced response,suggesting that NECA results in mass redistribution signals in both celllines through a dynamin-independent pathway. FIG. 61 shows the resultsof a GPCR agonist-induced directional mass redistribution within adlayerof quiescent A431 cells. Three GPCR agonists, bradykinin (100 nM),carbachol (10 μM) and clonidine (1 μM), induced time-dependent responsesof quiescent A431 cells, in comparison with that induced by EGF (8 nM).(F) Pretreatment of A431 with 10 μM AG1478 on the GPCR agonist- andEGF-induced responses.

FIG. 62 shows a schematic drawing shows the mechanism of EGF-inducedEGFR activation and GPCR agonist-induced EGFR transactivation. The EGFRhas been found to be a critical downstream element of signaling systems,including those employed by mitogenic G protein-coupled receptors(GPCRs), cytokine receptors, integrins and membrane-depolarizing orstress-inducing agents. Previous studies have shown that A431endogenously expresses bradykinin B₂ receptor, muscarinic receptor(s),and alpha 2 adrenergic receptor(s). Stimulation of quiescent A431 withGPCR agonists, bradykinin, clonidine and carbachol, results in twodistinct DMR response curves. Carbachol and clonidine stimulation led toresponses with almost identical features as those induced by lowconcentrations (2-8 nM) of EGF. As expected, pretreatment of A431 withAG1478 at 10 μM totally abolished the N-DMR phase, and significantlyreduced the kinetics of the P-DMR phase. In contrast, bradykininstimulation results in an extremely rapid P-DMR phase (within 100 sec),and a much shorter transition time Σ. The pretreatment of A431 withAG1478 can only partially attenuate the response. Consistent with thoseprevious studies by others, (i) stimulation with GPCR agonists couldcrosstalk with Ras-MAPK pathways through distinct mechanisms whichdepend on the context of specific cells, (2) the GPCR agonist-inducedEGFR transactivation can be examined using the resulted signatures ofthe Ras/MAPK activation. Since the GPCR agonist-triggered EGFRtransactivation leads to comparable DMR signals as EGF stimulation, thetransactivation acts as a signaling amplification mechanism such thatone can study GPCR signaling and screen agonists and antagonists againstan endogenous target GPCR in its native environment. The distinctkinetics of the DMR responses in response to different GPCR agonistsindicates that distinct GPCRs may transactivate the Ras/MAPK pathwaythrough distinct mechanisms, possibly depending on the G proteins thereceptor coupled and the cell context.

In FIG. 62 epidermal growth factor receptor (EGFR) signaling pathwaysare shown. Members of the EGFR family contain a cytoplasmic tyrosinekinase domain, a single transmembrane domain, and an extracellulardomain that is involved in ligand binding and receptor dimerization.Binding of ligand to EGFR leads to formation of homodimers orheterodimers of the receptor with other family members. Each dimericreceptor complex will initiate a distinct signaling pathway byrecruiting different Src homology 2 (SH2)-containing effector proteins.Dimerization results in autophosphorylation initiating a diverse arrayof downstream cellular signaling pathways. The activated EGF-R dimercomplexes with the adapter protein, Grb, coupled to the guaninenucleotide releasing factor, SOS. The Grb-SOS complex can either binddirectly to phosphotyrosine sites in the receptor or indirectly throughShc. These protein interactions bring SOS in close proximity to Ras,allowing for Ras activation. This subsequently activates the ERK and JNKsignaling pathways that, in turn, activate transcription factors, suchas c-fos, AP-1, and Elk-1, that promote gene expression and contributeto cell proliferation. EGF=epidermal growth factor, EGFR=epidermalgrowth factor receptor, Shc=src homology domain consensus, grb2=growthfactor receptor-bound protein 2, SOS=mammalian son of sevenless, Raf=Rasactivated factor, MEK=MAP kinase kinase, MAPK=mitogen activated proteinkinase, PI3K=phosphatidylinositol 3′ kinase, PIP2=phosphatidyl inositol3,4-diphosphate, PIP3=phosphatidyl inositol 3,4,5 triphosphate,PLCγ=phospholipase—γ, DAG=diacyl glycerol, IP3=inositol 3,4,5triphosphate, PKC=protein kinase C. In FIG. 61 GPCR agonist induced EGFRtransactivation is shown. Activation of Src family kinases byGPCR-stimulated transactivation of receptor tyrosine kinases. The bestunderstood mechanism of crosstalk between GPCRs and receptor tyrosinekinases involves the GPCR-stimulated proteolytic release of ligands,such as HB-EGF, following activation of membrane-associated ADAM familyMMPs. Transactivated EGF receptors (EGFR1/2) recruit Shc and theGrb2/mSos complex, allowing them to serve as platforms for theGPCR-induced assembly of a Ras activation complex. Transactivation ofEGF receptors accounts for GPCR-stimulated activation of the cRaf-1,MEK1/2, ERK1/2 MAP kinase cascade in many systems. Src family kinasesare activated in response to EGF receptor activation, and play anessential downstream role in this form of GPCR signaling. In addition,some evidence suggests that Src plays a role in the poorly understoodprocess of GPCR-stimulated MMP activation, particularly in the Gβγsubunit-dependent pathway

7. Example 7 Multimode Detection Methods

Grating coupler biosensors are evanescent-wave sensors based on theresonant coupling of light into a waveguide by means of a diffractiongrating. (See discussion of different biosensors herein). An example, ofa biosensor, the grating coupler sensor, typically consists of thecombination of a guiding multilayer and of a diffraction grating.Typically, a four layer waveguide biosensor consists of a thin film of ahigh refractive index (n_(F)) material with a thickness of d_(F) (e.g.,Nb₂O₅ of index about 2.36) on a substrate of lower index (n_(s)) (e.g.,1737 glass, Corning code with an index about 1.50) than the film, buthigher than the cover medium being the biological solution with indexaround 1.35 (n_(c)). The substrate is preferably transparent in order topermit light incidence from the substrate side. An adlayer ofbiologicals, immobilized on the waveguide film, with a refractive indexaround 1.4 (n_(A)) and a thickness d_(A). The biologicals immobilizedinclude, but not limited to, antibodies, antigens, receptors, peptides,phages, “single-stranded” DNA(RNA)-sections, genes, gene sections,targets, proteins, binding proteins, enzymes, inhibitors, nucleic acids,nucleotides, oligonucleotides, allergens, pathogens, carbohydrates,metabolites, hormones, active ingredients, molecules with low molecularweight, lipids, signal, cells, and bacteria.

The guided waves or modes in planar waveguide are TE_(m) (transverseelectric or s-polarized) and TM_(m) (transverse magnetic orp-polarized), where m=0, 1, 2, . . . is the mode number. A laserilluminates the waveguide at varying angles and light is coupled intothe waveguide only at specific angles determined by the effectiverefractive index of the guided mode. The laser light coupled propagatesparallel to the surface in the plane of a waveguide film creating anelectromagnetic field in the liquid adjacent to the interface. A givenmode type propagates only as a guide wave if two conditions need to befulfilled: (a) the refractive index of the waveguide film has to be atleast 1% larger than the surrounding substrate and cover mediumrefractive indices; and (2) the thickness of the waveguide film islarger than a well-defined value, call the cut-off thickness d_(C).

The waveguide grating biosensors consist of at least one waveguidegrating structure unit or of at least one sensor location. Thebiosensors can be associated with a microplate, each well containing atleast one waveguide grating structure.

Disclosed are methods wherein an analyte(s) in a sample is eitherunlabeled or labeled. When the analyte(s) is labeled, it can be labeledin any fashion, such as the moiety attached to the analyte(s) can emitfluorescence, chemiluminescence, bioluminescence, phosphorescence orelectro-luminescence on excitation with light (with a wide and/or narrowexcitation spectrum) or chemical/electrochemical activation. When theanalytes themselves are not labeled, a labeled binding partner that canbind to specific binding site(s) of the immobilized probe molecules withdesired affinity are used as a reference ligand. The reference ligand isused to determine relative activities or affinities of analytes againstthe probe molecules.

The label-independent detection of a binding of an analyte(s) and/or thereference ligand to immobilized probe molecules located at the gratingarea is based on the changes in wavelength or angle of reflected lightsdue to the refractive index changes (e.g., see U.S. Pat. No. 4,815,843,or U.S. Pat. No. 5,479,260). The label-dependent detection of binding ofthe reference ligand or the competitive binding of the analytes againstthe reference ligand to the probe molecules is based on the changes incolor (e.g., fluorescence, chemiluminescence, or bioluminescence,phosphorescence or electro-luminescence, etc).

The labeled dependent detection can be achieved by two distinctexemplary methods. In the first method, the waveguide grating substrateis used to propagate light within the waveguide film and at the sametime generate an evanescent wave penetrating the side of the probemolecules immobilized. The penetrated evanescent wave results inexcitation of the labeled analytes or the labeled reference ligand, withdifferent efficiency that is dependent on the distance between thelabeled molecules and the waveguide film surface. The closer the labeledmolecules are to the surface, the higher the efficiency of theexcitation. Particularly, the evanescent field excitation provides anenhanced excitation probability/efficiency of the surface-boundfluorophores along the entire planar waveguiding surface (Budach, W.;Abel, A. P.; Bruno, A. E.; Neuschafer, D.; “Planar Waveguides asHigh-Performance Sensing Platforms for Fluorescence-Based MultiplexedOligonucleotide Hybridization Assays” Anal. Chem. 1999, 71(16):3347-3355. and Edmiston, P. L.; Lee, J. E.; Wood, L. L.; Saavedra, S. S.“Dipole Orientation Distributions in Langmuir-Blodgett Films by PlanarWaveguide Linear Dichroism and Fluorescence Anisotropy” J. Phys. Chem.1996, 100: 775-784.). This is in contrast to luminescence detectionprinciples based on confocal microscopy, where the light source isfocused to a defined volume element leading to a strong local electricalfield (i.e., epifluorescence). By doing this, the waveguide gratingstructure becomes the core component for both detections:label-independent detection based on changes in the refractive index inthe propagation media of the evanescent field due to specific molecularadsorption at the sensor surface, and label-dependent detection based onchanges in color (intensity, intensity distribution, total internalreflection fluorescence intensity, etc) which offer superiorsensitivity, because of the fact that the evanescent wave decaysexponentially as the distance of a target or a target complex whether itis labeled or unlabeled is increased.

For this approach, the special sensor design is required forsimultaneously coupling the light into the waveguide and exciting thefluorescence moiety when the fluorescence-based detection is targeted. Agiven sensor with a unique structure (e.g., grating structure, periods,depths, properties and thickness of the waveguide film, configurationsof the sensor, etc) tends to allow a laser of specific wavelength to becoupled into the sensor at near the normal angle. This normal anglecoupling is preferred for cell sensing, since cells are covered withmedium as well as most liquid handling devices prefer the liquid changesat the normal angle. However, fluorescent molecules to be excitedgenerally require specific light sources with a particular range ofwavelength. For example, Cy3 requires the excitation light being in therange of 530-560 nm. In order to detect the DMR signal as well asfluorescence using same light source, the sensor need to be modeled suchthat it allows the coupling of the same light source into the waveguide.Thus the evanescent wave of the propagated light can be used to excitethe fluorescence molecules within the penetration depth or sensingvolume.

The second method involves a separate excitation light source tospecifically excite the bound labeled analytes or reference ligand(s),and a separate emission detection device to collect the emission light.This approach has less stringent requirements relating to waveguidesensor design, and can be applied to a wide range of different sensordesigns.

8. Example 8 Profiling of Endogenous GPCRs in A431 Cells

Dynamic redistribution of cellular contents, equivalent to dynamic massredistribution (DMR), is common to many cellular processes including thesignaling through G protein-coupled receptors (GPCRs) in response tostimulation. The DMR can be manifested by resonant waveguide grating(RWG) biosensors, and the resultant DMR signal offers a novel andintegrated readout for sensing living cells under real physiologicalconditions. Upon investigating the DMR signals of quiescent A431 cellsmediated through the activation of endogenous GPCRs using the RWGbiosensors in combination with a panel of GPCR agonists, a unique DMRsignature was identified for each class of GPCRs, based on the Gprotein(s) with which the receptor is coupled (i.e., Gq, Gs and Gi). TheDMR signals were dependent on the doses of agonists and the expressionlevels of endogenous receptors. The dose-dependent switching from onetype of DMR signal to another was observed for a small set of GPCRagonists. Together with its ability to map the network interactions andregulation of GPCR signaling, the label-free and non-invasive biosensorsenable real time kinetic measurements, thus allowing them to be used forGPCR drug discovery and deorphanization.

G-protein-coupled receptors (GPCRs) are a superfamily of membraneproteins that share common structural motifs with seven transmembranespanning domains, an extracellular N-terminus and an intracellularC-terminus. GPCRs have been implicated in the development andprogression of major diseases such as cardiovascular, respiratory,gastrointestinal, neurological, psychiatric and metabolic disorders.GPCRs represent the single largest family of druggable targets in humangenome and have been proven to be the most productive area for smallmolecule drug discovery, as illustrated by the fact that GPCRs accountfor ˜50% of the current drug targets with more than $60 billion in salesin 2000. Considering that the current GPCR-based drugs only target ˜25%of the approximately 200 known GPCRs, and there are ˜140 newlyclassified orphan receptors, GPCRs are a target class that offers ampleopportunities for drug discovery.

A diverse array of exogenous stimuli including light, ions,neurotransmitters and hormones modulate the physiology andpathophysiology of cells through GPCRs. The activation of GPCRs mediatedby agonists triggers the dynamic interaction with their associated Gproteins and other regulatory proteins, which governs the cascade ofintracellular responses. GPCRs can be divided into three groups,distinguished by their coupled G-protein subtype: G_(q), G_(s) andG_(i). The ligand-induced cellular events mediated through a GPCRtypically start with changes in receptor conformation andoligomerization state, followed by G protein activation (GDP-GTPexchanges on G_(α) subunit, G_(α) and G_(βγ) disassociation, G proteindecoupling from the receptor, generation of G_(α) and G_(βγ)-signalingcomplexes), and downstream signaling activation that leads to secondmessenger generation (Ca²⁺ mobilization, inositoltriphosphategeneration, and/or intracellular cAMP level modulation). Subsequently,GPCR signaling leads to expression of specific genes and desensitizationof GPCRs from the cell surface through endocytosis; many of whichinvolve dynamic trafficking of numerous intracellular proteins.Ultimately, the phenotypes, morphology and physical properties of thetarget cells are altered. The signaling and regulatory machineriesgenerally take a timely and precisely controlled action that governs thecellular responses. As a result, almost all GPCR signaling are common inthe sense that there are ordered and regulated dynamic redistribution ofcellular contents during the signaling cycle. Monitoring the dynamicredistribution of cellular contents should will insights in GPCRsignaling and a powerful means for GPCR screens.

a) Materials and Methods

(1) Materials

Adenosine amine cogener (ADAC), anandamide, ATP, interleukin-8 (IL-8),interferon-γ-inducible protein-10 (IP-10), oleoyl-L-α-lysophosphatidicacid (LPA), NECA, nocodazole, thrombin, trypsin, and UK14304 werepurchased from Sigma Chemical Co. (St. Louis, Mo.). A-77636, BRL 54443,clonidine, epinephrine, HTMT dimaleate, isoprenternol, oxotremorine M,oxymetazoline, and SKF38392 were obtained from Tocris Chemical Co. (St.Louis, Mo.). Fluo-3 was obtained from Molecular Probes (Eugene, Oreg.).Angiotensin II, apelin 1717, apelin 1-13, bombesin, bradykinin, DAMGO,dynorphin A, endothelin-1, galanin, GLIGKV-amide, GLIGLR-amide,glucagon, α-melanocyte stimulating hormone (α-MSH), motilin, neurokininA, neuromedin N, neuropeptide Y, neurotensin, nociceptin, SFFLR-amide,substance P, urotensin II, and YFLLNRP-amide were obtained from Bachem(King of Prussia, Pa.). Corning® Epic™ 96 well and 384 well biosensormicroplates were obtained from Corning Incorporated (Corning, N.Y.), andcleaned by exposure to high intensity UV light (UVO-cleaner, JelightCompany Inc., Laguna Hills, Calif.) for 6 minutes before use.

Human epidermoid carcinoma A431 cells (American Type Cell Culture) weregrown in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10%fetal bovine serum (FBS), 4.5 g/liter glucose, 2 mM glutamine, andantibiotics. ˜3-7.5×10⁴ cells at passage 3 to 5 suspended in 200 μl theDMEM medium containing 10% FBS were placed in each well of a 96 wellmicroplate. Similarly ˜1-2×10⁴ cells in 50 μl the growth medium wereplaced in each well of a 384 well microplate. After cell seeding, thecells were cultured at 37° C. under air/5% CO₂ until ˜95% confluency wasreached (˜2-4 days).

(2) Fluo-3 Ca²⁺ Mobilization Assay—

A431 at passage 3 to 5 were grown in Costar™ 96 well clear cell culturemicroplates until ˜95% confluency, washed twice and starved overnightwith the DMEM only, washed with 1×HBSS (1× regular Hank's balanced saltsolution, 20 mM HEPES buffer, pH 7.0) in the presence of 2.5 mMprobenicid, and labeled in the same buffer containing 4 μM Fluo-3 for 1hour at room temperature. The cells were then washed twice with buffer,maintained with 100 μl 1×HBSS containing 2.5 mM probenicid. The assaywas initiated by transferring 100 μl GPCR agonist solution to the cellplate, and calcium signal was recorded over 6 minutes with a 6 secinterval using HTS7000 BioAssay Reader (PerkinElmer Life Science,Boston, Mass.). The assays were carried out at room temperature in orderto allow direct comparison with optical sensing data.

(3) Dynamic Mass Redistribution (DMR) Optical Biosensor Assays

A Corning® Epic™ angular interrogation system with transverse magneticor p-polarized TM₀ mode was used for all studies. Several extra actionswere taken to minimize the unwanted effects. First, to minimize the bulkindex changes when a compound solution is introduced, 1×HBSS bufferwithout any probenecid was used to dilute all the compounds, whereas theDMEM buffer only was used to starve the cells. Secondly, to facilitatethe cell responses as well as to rapidly reach a steady state when thesensor plates having cells were placed in the system at roomtemperature, the cells were pre-starved with the DMEM buffer without anyFBS for a prolonged period of time (typically 20±2 hours), and thequiescent cells were directly used for assays without any wash. Thirdly,the DMSO concentrations in all compound solution were minimized to below0.05%, although higher concentrations of DMSO can be used in thedisclosed assays.

For kinetics measurements, the cultured cells (˜95% confluency) werestarved for about 20 hours with DMEM alone at 37° C. under air/5% CO₂.Afterwards, the sensor microplate containing cells was placed into theoptical system, and the cell responses were recorded before and afteraddition of a solution at room temperature. For compound studies, thecells in each well were pretreated with a compound solution of 50 μl orthe 1×HBSS until a steady phase (i.e., no obvious mass redistribution)was reached (generally within one hour), before GPCR agonist solution of50 μl was introduced. All studies were carried out at room temperaturewith the lid of the microplate on except for a short period of time(˜seconds) when the solution was introduced, in order to minimize theeffect of temperature fluctuation and evaporative cooling. The unit ofthe responses indicated herein was a change in pixel of the centralposition of the resonant band of each sensor as imaged by a CCD camera;1 unit equals to ˜5.82×10⁻⁴ refractive index changes, based on anexperimental normalization protocol, which uses theconcentration-dependent responses of both glycerol and dimethylsulfoxide. It is understood that other units can be determined based onoperating parameters and the needs of the assay as disclosed herein.

b) Results and Discussions

(1) Endogenous GPCRs and Their Signaling in A431 Cells

A431 cells were used as a model system to study the ligand-inducedoptical signatures of all three major types of GPCRs—G_(q), G_(s), andG_(i)-coupled receptors—under real physiological conditions. Theapproach was primarily based on known endogenous receptors in A431, incombination with random screening using a small library of well-knownagonists against many other different types of GPCRs. It is highlypossible that a particular GPCR could transduce signals through morethan one types of G proteins with which the receptor is coupled, andeven through other non-G protein signaling pathways.

The known endogenous GPCRs in A431 cells include bradykinin B₂ receptor,β₂ adrenergic receptor, adenosine receptors A₁, A_(2A) and A_(2B),histamine receptor H₁, protease activated receptors PAR₁ and PAR₂,purinergic receptors P2Y₁, P2Y₄, P2Y₆ and P2Y₁₁, LPA receptors LPA₁,LPA₂ and LPA₃, and bombesin receptor BRS₁. RT-PCR studies done by othershave shown that A431 endogenously expresses at least four family membersof P2Y receptors—P2Y₁ (relatively low), P2Y₄, P2Y₆ and P2Y₁₁, althoughother studies suggested that P2Y₂ is also endogenously expressed.

Among these receptors, B₂, P2Y receptors, PAR receptors, LPA₂ and LPA₃,and BRS₁ receptors are primarily G_(q)-coupled receptors, whereasA_(2A), A_(2B), and β₂ are G_(s)-coupled receptors. Little is known forthe signaling pathways of H₁ receptors in A431. Interestingly, there areonly few of literature reports for endogenous G_(i)-coupled receptors inA431. One example is A₁ receptor. Although LPA₁ is known to primarilylead to signaling through G_(i) pathway, there is no any literaturereport for the signaling mechanism of LPA₁ in A431.

(2) Optical Signatures of the Activation of Endogenous GPCRs in A431

The panel of agonists were used individually to stimulate quiescent A431cells. The dose-dependent and kinetic responses were recorded andanalyzed. In a typical kinetic measurement, the angular shift ofresonant lights of each sensor induced by an agonist is monitored inreal time and plotted as a function of time. An increased signal (P-DMR)means an increase in the amount of bio-molecules within the sensingvolume (˜120 nm); conversely, a decreased signal (N-DMR) means adecrease in the amount of bio-molecules within the sensing volume. Thesensing volume, also known as penetration depth, is an intrinsicproperty of the coupled light within the waveguide film, which createsan evanescent wave extending into the cell layer and the medium.

FIG. 63 showed four classes of optical responses of A431 cells mediatedby GPCR agonists. As shown in FIG. 63 a, the first class of opticalsignatures exhibited two major phases—a P-DMR phase with a rapidincreased signal (point A to B in FIG. 63 a) and a subsequent N-DMRphase with a slowly decayed signal (point B to C in FIG. 63 a). Agoniststhat result in such type of optical signature include B₂ receptoragonist bradykinin, P2Y receptors agonist ATP, and PAR agoniststhrombin, trypsin, GLIGLR-amide, GLIGKV-amide and SFFLR-amide. Theconventional Ca²⁺ mobilization assays using Fluo-3 showed that all ofthese agonists triggered a dose-dependent elevation of intracellularCa²⁺ level, as measured with the change in fluorescence intensity ofFluo-3 in cells. Together with the detailed analysis of cellularmechanisms for bradykinin-mediated A431 responses, these resultssuggested that this type of optical signature is attributed to theactivation of G_(q)-coupled receptors, which leads to rapid Ca²⁺mobilization and downstream signaling events.

The second class of optical signatures exhibited one major phase (FIG.63 b)—a P-DMR phase with a slowly increased signal until it reaches anevaluated plateau (point B to C in FIG. 63 b). In many cases there is aninitial phase with a slowly decreased signal and small amplitude, whichoccurs right after the introduction of agonist solution (point A to B inFIG. 63 b). The time to complete the initial phase generally is muchlonger than those induced by the introduction of compound solutions(˜seconds). When a compound solution was added, the unmatched refractiveindices between the compound solution and the DMEM medium if any wouldresult in a rapid phase relating to the bulk index change. Agonists thatresult in such type of optical signature include β₂ agonists epinephrineand isoprenternol, and A_(2A) and A_(2B) agonist NECA. The conventionalCa²⁺ mobilization assays showed that all of these agonists did nottrigger any significant changes in intracellular Ca²⁺ level (data notshown). On the other hand, either of the two adenylate cyclaseactivators forskolin and NKH447 resulted in an optical signature that issimilar to those induced by either β₂ or A₂ agonists (FIG. 64). Bothchemicals are known to activate adenylate cyclase, leading to theincrease in the intracellular level of cAMP—a second messenger inG_(s)-coupled receptor signaling. The pretreatment of quiescent cellswith 10 μM forskolin or NKH447 completely abolished the DMR responsesmediated by epinephrine (FIG. 65), indicating that both compoundsresulted in a cellular response sharing same downstream signalingpathway(s) with these agonists. These results suggested that this typeof optical signature is attributed to the activation of G_(s)-coupledreceptors, which leads to accumulation of intracellular cAMP anddownstream signaling events.

The third class of optical signatures exhibited two consecutive P-DMRevents (FIG. 63 c)—a rapid P-DMR phase that leads to an elevated level(point A to Bin FIG. 63 c), and a subsequent P-DMR phase with a slowlyincreased signal until it reaches another elevated plateau (point B to Cin FIG. 63 c). Among these agonists that target known endogenous GPCRs,only LPA receptor agonist LPA at the doses below about 500 nM resultedin this type of optical signature. Other agonists that also triggeredthis type of response include MC receptors α-MSH. This type of opticalsignature can be attributed to the activation of G_(i)-coupledreceptors, since it shares unsurprised similarity to that ofG_(s)-coupled receptors. Both G_(i) and G_(s) signaling lead to themodulation of intracellular cAMP but in an opposite way.

The fourth class of optical signature did not exhibited any significantDMR signals (FIG. 63 d), which was similar to that induced by the HBSSalone. Each agonist was examined typically at five different dosesbetween 1 nM and 10 μM, and at least two independent experiments werecarried out to ensure the results. Agonists that fall into this categoryinclude A-77636, SCH23390 and SKF38392 (DRD1), anandamide (CNR1 andCNR2), Angiotensin II (AGTR1), apelin 1-17 and apelin 1-13 (AGTRL1), BRL54443 (HTR1E/F), clonidine and UK14304 (ADRA2A, B and C), DAMGO anddynorphin A (OPRM1 and OPRK1), endothelin-1 (EDNRA and EDNRB), galanin(GALR1 and GALR2), glucagon (GCGR), interleukin-8 (CXCR1), IP-10(CXCR3), motilin (MOTR), substance P (TACR1), neurokinin A (TACR2),neuromedin N and neurotensin (NTSR1), neuropeptide Y (NPY1, 2, 4, 5,6R), nociceptin (OPRL1), oxymetazoline (ADRA1A), and urotensin II(GRP14). The targeted receptor(s) of these agonists were indicated inthe parentheses. That no significant DMR signals resulted from theseagonists indicated that there are no or relatively low expression levelsof their corresponding receptor(s) in A431 cells. The little DMR signalsresulted from IL-8 stimulation (data not shown) suggested thatrelatively low level of endogenous CXCR1 is expressed in A431 cells.Another possibility is that there is low-constitutive secretion of IL-8from A431 cells.

Bombesin receptor subtype 1 (BRS₁) was also previously reported toendogenously express in A431 cells. Fluo-3 assays showed that bombesinled to a maximum increase in intracellular Ca²⁺ level of 20±5% (n=5;data not shown), suggesting that bombesin triggers G_(q)-signaling. Asexpected, the stimulation of quiescent A431 with bombesin led to adose-dependent G_(q)-type optical signature (data not shown), but withmuch smaller amplitudes than those mediated by bradykinin, ATP or eitherof PAR agonists. The apparent IC₅₀ was found to be approximately 1 nM.The small amplitude of the DMR signals induced by bombesin suggested therelatively low expression of BRS1 in A431.

(3) Determination of Agonist Efficacies to Activate Endogenous GPCRs inA431

Next, the efficacies of these agonists that result in significant DMRsignals were examined. Since in some cases more than one subfamilyreceptors are endogenously expressed in A431, and a particular agonistcould activate multiple of subfamily receptors with differentefficacies, a 5× concentration series of agonist solution was initiallyused to examine the cellular responses. In most cases a 2× concentrationseries of agonist solutions were further used to accurately determinethe EC₅₀ value of the agonist. The amplitudes of DMR signals wereplotted as a function of agonist concentration, and analyzed with Prismto calculate the EC₅₀.

FIG. 66 summarized the dose-dependent responses induced by agonists thattarget endogenous G_(q)-coupled receptors. Since analysis of theamplitudes of both P-DMR and N-DMR signals as a function of agonistconcentration result in almost identical EC₅₀, only the P-DMR signalswere plotted and the resultant efficacies of agonists were discussed.All saturation curves fit well with one-binding site non-linearregression, leading to an apparent EC₅₀. The apparent EC₅₀ value wasfound to be 2.2±0.6 μM (n=3), 10.0±1.2 mM (n=−3), and 9.6±2.0 unit/ml(n=3) for ATP, bradykinin and thrombin, respectively. In comparison, theEC₅₀ values of these agonists were also determined using Ca²⁺ fluxassays (data not shown) and found to be consistent with those obtainedwith the optical biosensor assays. Extracellular ATP has been shown tobe a potent agonist of both ionotropic P2X and G protein-coupled P2Yreceptors. Because the RWG biosensor is most sensitive to theredistribution of cellular bio-macromolecules rather than ions and theATP-mediated optical signatures are similar to those induced bybradykinin and PAR agonists, it was reasoned that endogenous P2Yreceptors primarily account for the DMR signals induced by ATP. On theother hand, B₂ but not B₁ receptor is endogenously expressed in A431 andB₂ receptor accounts for most of the physiological andpathophysiological action of bradykinin. Thrombin is an agonist forPAR₁, and SLIGLR-amide and SLIGKV-amide are PAR₂-specific agonists.However, SFFLR-amide and trypsin apparently activate both PAR₁ and PAR₂.

FIG. 67 summarized the dose-dependent responses induced by agonists thatactivate endogenous G_(s)-coupled receptors. Here the amplitudes of theslowly increased P-DMR signals were plotted as a function of agonistconcentration. The apparent EC₅₀ value was found to 21.5±1.2 nM (n=3),and 6.0±1.4 nM (n=3) for NECA and epinephrine, respectively. NECA is anagonist for A_(2A), A_(2B), and A₁ receptors with an affinity of 20,330, and 14 nM, respectively. Coexisting A₁ and A₂ adenosine receptorswith opposite actions on adenylate cyclase activity has been describedin several cell lines including A431. In A431, adenosine evoked abiphasic response in which low doses (<˜10 μM) produced inhibition ofcolony formation through A₁ receptor but higher concentrations (up to100 μM) progressively reversed this inhibition through A₂ receptor. Suchdual effect thus affords the opportunity for reciprocal control andfine-tuning the signaling pathways. Since NECA has similar affinities toA₁ and A_(2A), the optical signatures induced by NECA indicated thatG_(s) signaling is dominated. To further discriminate the effect,adenosine amine cogener (ADAC), an adenosine receptor selective agonistwith an affinity of 0.85, 210, and 285 nM to A₁, A_(2A), and A₃receptor, were used respectively. We were particularly interested inhigh doses of ADAC. Results showed that at high doses (>50 nM) ADACstimulated a typical G_(s)-type optical signature in a dose-dependentmanner, with an apparent and effective EC₅₀ of 3.7±1.1 μM (n=3). On theother hand, since A431 endogenously expresses high numbers Of β₂receptor (˜40,000 copies per cell), the epinephrine-induced DMR signalsobserved are specific to the activation β₂. Epinephrine binds to β₂ witha EC₅₀ of 5-20 nM.

FIG. 68 showed the dose-dependent responses induced by α-MSH. Here thetotal responses of two P-DMR events were plotted as a function ofagonist concentrations. The apparent EC₅₀ value was found to 9.0±1.6 nM(n=3) for α-MSH, consistent with the literature values.

We here systematically examined the optical signatures of quiescent A431cells stimulated with a panel of agonists that target a wide variety ofGPCRs. The choice of agonists was partly based on the known endogenousGPCRs in A431. The results showed that the optical signatures mediatedby those agonists fall into three major categories (FIGS. 63 a,b and c),besides the fourth type of optical signatures that is similar to thattreated with the vehicle (i.e., HBSS) only (FIG. 63 d). Three differentstrategies were employed to clarify the cellular signaling mechanismsaccount for these optical signatures. First, the conventional secondmessenger assays (i.e., Fluo-3 assays) were used to classify theagonists for their ability to cause Ca²⁺ mobilization. Second, twoadenylyl cylase (AC) activators, forskolin and NKH447, were used tostimulate the quiescent A431 cells. The similarity between GPCRagonist-mediated and adenylate cyclase activator-mediated opticalsignatures was examined and used to point out the G_(s)-mediatedsignaling. Third, a systematic mapping of the effect of a panel ofwell-known modulators on the optical signatures induced by a specificagonist was carried out to investigate its cellular mechanisms andsignaling network interactions. Based on these studies, the three majorclasses of optical signatures were assigned to three classical types ofGPCR signaling: G_(q)-, G_(s)-, and G_(i)-signaling. Because of thelimit information of endogenous G_(i)-coupled receptors in A431 cells,the G_(i)-type optical signature need to be further confirmed, althoughthe dose-dependent responses induced by HTMT strongly supported suchindication.

Except of IL-8, all agonists that target all known endogenous GPCRs inA431 had led to significant DMR responses. Their efficacies determinedwith the RWG biosensors were consistent with either Fluo-3 assay resultsif applicable or literature reports, suggesting that the MRCAT can beused to accurately determine the agonist efficacies.

(4) Signature Switching of Agonist-Mediated Cell Responses—

GPCR signaling is complicated, depending on the cellular states andcontext, the selectivity of agonists, and the expression level and typeof the receptor. Depending on the cellular states and context, theactivation of a particular GPCR could trigger the cellular responsesthrough more than one type of G proteins. For example, the activation ofendogenous bradykinin B₂ receptor induced by bradykinin mediates thecellular signaling through both G_(q) and G_(s)-pathways in A431 cells;both signaling pathways cross-regulate each other. It was found hereinthat the signaling mediated through B₂ receptor is dependent on thecellular status of A431 cells as well as the doses of bradykinin. Inproliferating states, low doses (<100 nM) of bradykinin preferablytrigger G_(s)-mediated signaling, when high doses (>100 nM) ofbradykinin favors G_(q)-signaling. One the other hand, bradykininbetween 0.5 nM and about 100 nM mediated both G_(s) and G_(q)-pathways,when it was used to stimulate the quiescent A431 cells obtained with0.1% FBS for about 20 hours. Conversely, the fully quiescent A431,obtained with the DMEM medium in the absence of any FBS or other growthfactors for about 20 hours, responded to bradykinin at all doses withpredominantly G_(q)-signaling (data not, shown).

It was identified that a few of the agonists including LPA and HTMTtriggered DMR signals that exhibited relatively complicateddose-dependence. FIG. 69 showed the dose-dependent responses induced byLPA. The fully quiescent A431 cells responded to LPA stimulation withtypical G_(i)-type optical signature at low doses of LPA, andprogressively switched to G_(q)-type optical signature at high doses ofLPA. One possibility is that LPA at low doses preferably activated LPA₁receptor that leads to G_(i)-mediated signaling. When the concentrationof LPA increases, the endogenous LPA₂ and LPA₃ receptors becomeactivated, leading to the G_(q)-mediated signaling.

FIG. 70 showed the dose-dependent optical signals induced by HTMT. HTMTis an agonist of H₁ and H₂ receptors. At low doses (<˜40 nM), HTMTdose-dependently resulted in a typical G_(i)-type optical signature(FIG. 70 b). As the concentration of HTMT continues to increase up toaround 80 nM, the optical signature relating to DMR started to decreaseand became almost steady (i.e., no obvious DMR). Further increase in theconcentration of HTMT resulted in the switching to a typical G_(s)-typeoptical signature (FIG. 70 b). The amplitude of the P-DMR signals wasplotted as a function of HTMT concentration, and clearly showed theswitching (FIG. 73 c). Since G_(s) signaling leads to the accumulationof intracellular cAMP and G_(i) signaling causes the opposite effect, itis reasonable to speculate that HTMT activates both G_(s) andG_(i)-signaling pathways with different efficacies, possibly throughdistinct receptors. The delicate balance between G_(s) and G_(i)signaling determines the net cellular responses, at least in terms ofdynamic mass redistribution as monitored by the RWG biosensor.

9. Example 9 Probe the Cross-Communication Between Different Targets

It is common that there is cross-communication among distinct targets,and even more common among the members of a subfamily of targets. Forexample, EGFR can be transactivated by certain GPCR agonists. Again, anactivator of one target (e.g., GPCR) can activate other closely relatedtarget.

Protease activated receptors (PARs) comprise a novel family of Gprotein-coupled receptors (GPCRs) which to date include PAR1, PAR2, PAR3and PAR4. Instead of being activated through reversible ligand binding,PARs utilize a unique proteolytic mechanism for activation. Serineproteases such as thrombin and trypsin site-specifically cleave thereceptor within the extracellular N-terminal exodomain. The activatingcleavage site is the residue 41-42 (R↓SFLLRN), 36-37(R↓SLIGKV), 38-39(K↓TFRGAP) and 47-48 (R↓GYPGQV) in humans for PAR1, PAR2, PAR3 and PAR4,respectively. The cleavage unmasks a new N-terminus, which in turn actsas a tethered ligand sequence. The tethered ligand domain bindsintramolecularly to and activates the receptor, thus initiatingsignaling. The proteases that activate PARs include coagulation factors(e.g. thrombin, coagulation factors VIIa and Xa), proteases frominflammatory cells (mast cell tryptase, neutrophil cathepsin G) andenzymes from epithelial tissues (trypsins). Three of the four PARs(PAR1, PAR3, and PAR4) are activated principally by thrombin, while PAR2is activated by trypsin-like proteases such as mast cell tryptase andcoagulation Factor Xa. Synthetic peptides (PAR-activating peptides orPAR-APs), corresponding to the first five or six amino acids of thetethered ligand sequences, can directly activate PARs, except for PAR3.Since these synthetic peptides function as receptor agonistsindependently of proteolysis, PAR-APs are useful for studying thephysiological and pathophysiological functions of PARs.

PARs are found in a large variety of normal and malignant tissues andcells including skin, platelets, endothelial cells, gastrointestinaltract, brain and lungs. Most cell types express multiple PARs. Oneexample is A431 cells which endogenously express PAR1 and PAR2. However,little is known for the signaling pathways of PARs in A431 cells,although epideriomoid carcinoma cells express several serine proteasesincluding human airway trypsin-like protease that may be potential PARactivators.

a) Materials and Methods

(1) Regents—

Thrombin, trypsin, latrunculin A, cytochalasin B, phalloidin,nocodazole, methyl-β-cyclodextrin (mβCD), α-cyclodextrin (αCD),N-benzoyl-L-arginine ethyl ester (BAEE) and epidermal growth factor(EGF) were purchased from Sigma Chemical Co. (St. Louis, Mo.). KN-62 andGF109203x were obtained from Tocris Chemical Co. (St. Louis, Mo.).Fluo-3 and Texas Red-phalloidin (TR-phalloidin) was obtained fromMolecular Probes (Eugene, Oreg.). SFFLR-amide, GLIGKV-amide,GLIGLR-amide, bradykinin, and YFLLNRP-amide were obtained from Bachem(King of Prussia, Pa.). Corning® Epic™ 96 well biosensor microplateswere obtained from Corning Inc (Corning, N.Y.), and cleaned by exposureto high intensity UV light (UVO-cleaner, Jelight Company Inc., LagunaHills, Calif.) for 6 minutes before use.

(2) Cell Culture

Human epidermoid carcinoma A431 cells (American Type Cell Culture) weregrown in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10%fetal bovine serum (FBS), 4.5 g/liter glucose, 2 mM glutamine, andantibiotics. ˜3-7.5×10⁴ cells at passage 3 to 5 suspended in 2001 theDMEM medium containing 10% FBS were placed in each well of a 96 wellmicroplate, and were cultured at 37° C. under air/5% CO₂ until ˜95%confluency was reached (˜2-4 days).

(3) Fluo-3 Ca²⁺ Mobilization Assay

A431 at passage 3 to 5 were grown in Costar™ 96 well clear cell culturemicroplates until ˜95% confluency, washed twice and starved overnightwith the DMEM only, washed with 1×HBSS (1× regular Hank's balanced saltsolution, 20 mM HEPES buffer, pH 7.0) in the presence of 2.5 mMprobenicid, and labeled in the same buffer containing 4 μM Fluo-3 for 1hour at room temperature. The cells were then washed twice with buffer,maintained with 100 μl 1×HBSS containing 2.5 mM probenicid. The assaywas initiated by transferring 50 μl PAR agonist solution to the cellplate, and calcium signal was recorded over 6 minutes with a 6 secinterval using HTS7000 BioAssay Reader (PerkinElmer Life Science,Boston, Mass.). The assays were carried out at room temperature in orderto allow direct comparison with optical sensing data.

(4) Dynamic Mass Redistribution (DMR) Optical Biosensor Assays

Corning® Epic™ angular interrogation system with transverse magnetic orp-polarized TM₀ mode was used for all studies. After culturing, thecells (˜95% confluency) were starved for about 20 hours with DMEM alone,washed twice and maintained with 100 μl DMEM. Afterwards, the sensormicroplate containing cells was placed into the optical system, and thecell responses were recorded before and after addition of a solution.For compound studies, the cells in each well were pretreated with acompound solution of 50 μl or the 1×HBSS until a steady phase (i.e., noobvious mass redistribution) was reached (generally within one hour),before PAR agonist solution of 50 μl was introduced. The compound or PARagonist solutions were made in 1×HBSS in order to match the refractiveindex between the cell medium and compound solution, thus minimizing theunwanted effect of bulk index change due to the introduction of compoundsolution which can temporarily overwhelms any DMR signal as it occurs.All studies were carried out at room temperature with the lid of themicroplate on except for a short period of time (˜seconds) when thesolution was introduced, in order to minimize the effect of temperaturefluctuation and evaporative cooling. The unit of the responses indicatedthroughout this paper was a change in pixel of the central position ofthe resonant band of each sensor as imaged by a CCD camera; 1 unitequals to ˜5.82×10⁻⁴ refractive index changes, based on an experimentalnormalization protocol, which uses the concentration-dependent responsesof both glycerol and dimethyl sulfoxide.

(5) Fluorescence Imaging

Cells were grown on Corning® Epic 96 well biosensor microplates, starvedfor overnight with serum-free DMEM medium, chased with either trypsin orthrombin for certain time, fixed with 4% paraformaldehyde, permeabilizedin phosphate-buffered saline (PBS) containing 0.2% Triton, and blockedwith 1% bovine serum albumin (BSA). Afterwards, cells were incubatedwith 0.5 μM Texas Red-labeled phalloidin for 1 h at room temperature,and washed. After final washes and mounting, cells were examined with a40× objective, equipped in a Zeiss Axioplan fluorescence microscope.

b) Results

(1) PAR Agonists Mediate Elevation of Intracellular Ca²⁺ in A431 Cells

In quiescent A431 cells, thrombin, trypsin, PAR1-AP (SFFLR-amide), andPAR2-APs (GLIGKV-amide and GLIGLR-amide) all induced a rapid andtransient increase in intracellular Ca²⁺ ([Ca²⁺]_(i)) in aconcentration-dependent manner, as measured with the increase of Fluo-3fluorescence intensity. The saturation curves mediated by all PARagonists seem fit very well with one-site binding, based on non-linearregression and Scatchard analysis. The EC₅₀ was found to be 6±1 unit/ml(equivalent to 60±10 nM), 5.0±0.4 μM, 45.7±5.8 nM, 2.5±0.3 μM, and3.8±0.4 μM for thrombin, SFFLR-amide, trypsin, SLIGLR-amide, andSLIGKV-amide, respectively. The maximal [Ca²⁺]_(i) elevation induced bythrombin, SFFLR-amide, trypsin, SLIGKV-amide, and SLIGLR-amide was foundto be 48.2±3.5%, 74.3±3.9%, 100±6.3%, 52±6.3%, and 64±3.7%, respectively(FIG. 71). The maximal [Ca²⁺]_(i) elevation obtained with trypsin wasapproximately 2 fold as high as that obtained with thrombin. On theother hand, the maximal [Ca²⁺]_(i) elevation obtained with trypsin wasalso much higher than those obtained with two PAR2-APs. Furthermore,stimulation of A431 with a mixture of SFFLR-amide (20 μM) andSLIGKV-amide (20 μM) induced a [Ca²⁺]_(i) elevation of 102±5.4%, similarto that obtained with 200 nM trypsin alone. Interestingly, a PAR1specific partial agonist YFLLRNP at concentrations up to 160 μM did notinduce any significantly elevation of [Ca²⁺]_(i), but the pretreatmentof cells with 80 μM YFLLRNP suppressed the [Ca²⁺]_(i) elevation mediatedby 200 nM trypsin (48.3±4.5%, n=5). YFLLRNP at appropriateconcentrations (<˜100 μM) was found to selectively activate theG_(12/13) signaling cascade through PAR1 resulting in platelet shapechange, without stimulating the G_(q) or G_(i) signaling pathways inhuman platelets. These results suggest that trypsin can activate PARsother than PAR2. The concentrations required to induce a maximalresponse were 40 unit/ml, 20 μM, 400 nM, 20 μM, and 20 μM for thrombin,SFFLR-amide, trypsin, SLIGKV-amide, and SLIGLR-amide, respectively.

(2) PAR Agonists Mediate the Reorganization of Actin Filaments in A431Cells

The activation of PARs are known to lead to the reorganization ofcytoskeleton structure in several cell lines such as LNCaP, possiblythrough the activation of the Rho family proteins. The effect of PARagonists on the cytoskeleton structure of cells at high confluency(>90%) was investigated because of the unique design of our opticalsensing system which uses a band of light (a dimension of 200×3000 μmNote: this is the current configuration in our angular interrogation;the size of light used for illumination is typically in the range of ˜50μm to 5 mm) to illuminate each biosensor (meaning that the opticalsignature relating to DMR is an average of all cells within theilluminating area). Stimulation of quiescent A431 cells at confluency of˜95% with either thrombin or trypsin induced the reorganization of actinfilaments, as showed by the Texas Red-X-phalloidin staining pattern(data not shown). Resting A431 cells showed a typical stainingpattern—the actin filaments appear mostly elongated and evenlydistribute throughout the cytoplasm. Cells treated with 100 nM trypsinor 40 unit/ml thrombin triggered significant cytoskeletal reorganizationafter about 10 min (data not shown), and become obvious after about 30min. The actin filaments became predominately concentrated around therim of the cells 30 min after being stimulated with either thrombin ortrypsin. These results demonstrated that both thrombin and trypsinmediate the reorganization of actin filaments in A431 cells.

(3) PAR Agonists Mediate Significant Dynamic Mass Redistribution in A431Cells

Disclosed herein it was demonstrated that either one of the five PARsagonists examined results in a G_(q)-type optical signature, which allare saturable to agonist concentration. Similar to the Ca²⁺ mobilizationresults, the saturation curves of PAR agonist-mediated DMR signalsobtained with the optical biosensor assays also fitted very well withone-site binding model, based on the non-linear regression and Scatchardanalysis. It is worth noting that for trypsin, the DMR signals inducedby trypsin at low doses (<200 nM) were focused on because trypsin athigh doses (>2000 nM) leads to significant cell detachment from thesurface of the biosensors (data not shown).

Since many important aspects of cell activities including trafficking,signaling and morphological changes require the rearrangement ofcytoskeleton structure, the roles of cytoskeletal modulation in the PARagonist-induced optical responses (FIG. 72) were investigated.Pretreatment of A431 with latrunculin A completely blocked eitherthrombin- or trypsin-mediated DMR signal, while cytochalasin B was muchless effective in suppressing the responses. It is known that the twoagents utilize distinct mechanisms to cause actin disassembly:cytochalasin B caps actin filaments, while latrunculin A sequestersactin monomers. Such a difference may lead to distinct abilities foreach toxin to modulate the receptor signaling by either affecting theendocytosis or the assembly of signaling machineries. Conversely,neither a stabilizing polymeric F-actin agent phalloidin nor amicrotubule disrupter nocodazole had significant effect on boththrombin- and typsin-mediated responses.

PAR intracellular signaling leading to Rho activation that regulates thecytoskeletal reorganization appears to involve two major signaltransduction pathways: the G_(q)-coupled pathway resulting inphosphoinositol hydrolysis and calcium-dependent Rho activation, and thecalcium-independent direct activation of Rho through G_(12/13)-coupledp115Rho-GEF. Thus the effect of modulators that target Ca²⁺ signalingwas examined. The modulators used were a potent PKC inhibitor GF109203xand a potent Ca²⁺/calmodulin-dependent protein kinase II (CaMKII)inhibitor KN-62 (FIG. 73). GF109203x had no obvious effect on boththrombin- and trypsin-mediated DMR signal. However, KN-62 pretreatmentaffected the DMR signal mediated by thrombin and trypsin differently.When KN-62 slightly suppressed the thrombin-mediated DMR signal, italmost completely abolished the trypsin-mediated DMR signal. To examinethe possibility of KN-62 directly inhibiting the trypsin activity, theBAEE hydrolysis assay was used. Results showed that the presence ofKN-62 has no any obvious effect on the trypsin activity (data notshown).

The effect of PAR1 specific partial agonist YFFLRNRP which is previouslyshown to activate G_(12/13) resulting in the cell shape change, but notG_(q)-mediated Ca²⁺ signaling in human platelets was also examined.YFFLRNP only at high doses stimulated significant DMR signals (data notshown). YFFLRNP dose-dependently suppressed the DMR signals mediated bythrombin-, SFFLR-amide- and trypsin (FIG. 74). At the highest doseexamined, YFFLRNP almost completely blocked the thrombin-mediated DMR,but only partially attenuated both SFFLR-amide and trypsin-mediated DMR.Conversely, YFFLRNP has no obvious effect on the PAR2-AP GLIGKV-mediatedDMR signal. Collectively, these results suggested that the cytoskeletalreorganization is mainly resulted from the G_(q)-mediated Ca²⁺ signalingthrough PAR2 activation, but a Ca²⁺-independent mechanism through PAR1activation.

(4) Receptor Desensitization and Cross Desensitization of PAR Agonists

Since A431 endogenously expresses at least PAR1 and PAR2, and eitherthrombin or trypsin potentially activates more than one receptors, thedesensitization and cross desensitization of receptors in response tosubsequent stimulation of various combinations of PAR agonists, asevaluated by the extent of [Ca²⁺]_(i) elevation with Fluo-3 or the DMRsignal with optical biosensors was examined. The intervals were 6 minfor Ca²⁺ mobilization assays, and about 1 hour for DMR optical assays.

FIG. 75 summarized the main results of [Ca²⁺]_(i) in A431 sequentiallystimulated in various combinations of PAR agonists. Once A431 cells werestimulated with trypsin, the subsequent application of other PARagonists (40 unit/ml thrombin, 20 μM SFFLR-amide, 20 μM GLIGKV-amide, 20μM GLIGLR-amide, or 200 nM trypsin) induced almost no [Ca²⁺]_(i)elevation (FIG. 75 a-c, data not shown). Conversely, neither of PARagonists examined had any effect on the [Ca²⁺]_(i) elevation mediatedwith subsequent stimulation with bradykinin, an agonist for B₂ receptorwhich is endogenously expressed in A431 cells (exampled in FIG. 79 d),suggesting that the inhibition of the response to PAR agonists by thepreceding stimulation with trypsin was not due to the non-specificdigestion of the membrane proteins. On the other hand, the precedingstimulation with 40 unit/ml thrombin totally blocked the [Ca²⁺]_(i)elevation mediated by 40 unit/ml thrombin, but slightly suppressed thetrypsin-induced [Ca²⁺]_(i) elevation, whereas the preceding stimulationwith SFFLR-amide, GLIGKV-amide or GLIGLR-amide significantly attenuatedbut not completely eliminates the trypsin-induced [Ca²⁺]_(i) elevation(FIG. 79 e-g; data not shown). Furthermore, after the precedingstimulation with thrombin, PAR2-AP SLIGKV-amide induced the [Ca²⁺]_(i)elevation (48.5±3.8%) similar to that obtained without the precedingstimulation (52.0±6.3%). Conversely, the preceding stimulation withthrombin only partially block the [Ca²⁺]_(i) elevation induced bySFFLR-amide (32±4.3%), consist with the previous observations done byothers that SFFLR-amide may activate both PAR1 and PAR2. [Blackhart, B.D.; Emilsson, K.; Nguyen, D.; Teng, G. W.; Martelli, A. J.; Nysted, S.;Sundelin, J.; Scarborough, R. M. J. Biol. Chem. 1996, 271, 16466-16471].Thus trypsin desensitized the responsiveness to both PAR1-AP andPAR2-APs, whereas thrombin did not desensitize the responsiveness toPAR2-APs.

FIG. 76 summarized the main results of DMR responses of A431sequentially stimulated in various combinations of PAR agonists, asmonitored in real time using the RWG biosensors. The precedingstimulation with trypsin completely eliminated the DMR signal induced byeither trypsin (data not shown) or thrombin (FIG. 76 a), while itsignificantly suppressed the DMR signal induced by either of threePAR-APs (SFFLR-amide, GLIGKV-amide, GLIGLR-amide) (FIG. 76 b-c, data notshown). Conversely, trypsin pretreatment has little effect on the DMRmediated by bradykinin (FIG. 76 d). On the other hand, the precedingstimulation with thrombin, SFFLR-amide, GLIGKV-amide or GLIGLR-amidesignificantly suppresses but not completely eliminates thetrypsin-induced DMR signal (FIG. 76 e-g; data not shown). Furthermore,after the preceding stimulation with thrombin, two PAR2-APs(SLIGKV-amide and SLIGLR-amide) induced the DMR signal similar to thatobtained without the preceding stimulation (data not shown). In summary,these results indicated that thrombin primarily activates PAR1, whiletrypsin activates both PAR1 and PAR2.

(5) The [Ca²⁺]_(i) Elevation and DMR Signals Mediated by Both Thrombinand Trypsin are Sensitive to Cholesterol Level in Cells

Since cell cholesterol level is important to many cell functionsincluding GPCR signaling, the effect of cholesterol depletion by mβCD onboth intracellular Ca²⁺ elevation and DMR responses mediated by thrombinand trypsin was examined. The pretreatment of quiescent A431 cells withmβCD led to a dose-dependent suppression of [Ca²⁺]_(i) elevationmediated by either trypsin or thrombin (data not shown). Bothdose-dependent suppression curves fit very well with the one-phase decaynon-linear regression; consistent with the fact that mβCD results in therapid effluxing of cell membrane cholesterol molecules. On the otherhand, the inactive cyclodextrin steroisome αCD up to 8 mM had no effecton both trypsin and thrombin-induced responses (data not shown).

Similarly, the pretreatment of A431 with mβCD also led to adose-dependent alteration of the optical signatures induced by thrombinor trypsin (FIG. 77). Unlike the suppression of thrombin-mediated DMR bymβCD that exhibited dose-dependence similar to that measured with Ca²⁺mobilization, the suppression of trypsin-mediated DMR by mβCD showedcomplicate nature—a slow decayed attenuation to increased doses of mβCD.This difference suggested that the trypsin-mediated DMR signals involvemore complicated cellular mechanisms than that induced by thrombin.Conversely, the inactive cyclodextrin steroisome αCD up to 8 mM hadlittle effect on both agonist-induced DMR responses. However, high dosesof αCD (>10 mM) resulted in significant amounts of cells detached fromthe surface of the biosensors (data not shown). The functional recoveryof PARs after cholesterol depletion with mβCD was also examined. Thisexperiment was based on the timely recovery of cell surface cholesterolin the mβCD-treated cells after the removal of medium containing mβCD.To do so, the quiescent A431 cells were treated with 5 mM mβCD for 15minutes to ensure the removal of cell surface cholesterol content,followed by washing the treated cells three times with the DMEM mediumonly. The cells were then maintained with 100 μl the medium, and placedinto the optical systems. After incubation for 15 minutes to allow cellsreaching reasonably steady state, a 100 μl solution of thrombin at 80unit/ml was added to each well at specific time. The optical responseswere recorded throughout the assays. As shown in FIG. 78, resultedshowed that the thrombin-induced DMR signals were dependent on the timeafter the cell surface cholesterol was removed. The thrombin-induced DMRsignals progressively recovered until it reaches to the original levelobtained without cholesterol removal. The time-dependent recovery of thethrombin-induced optical signatures strongly implied that the formationof cholesterol-assisted microdomains is dynamic and reversible, andcholesterol concentration at the cell membranes is important inregulating the PAR signaling.

(6) The Cross-Communication Between EGFR and PARs

Since certain GPCR agonists transactivate EGFRs, the effect of EGF onPAR signaling was examined. The preceding stimulation with EGF hadlittle effect on the [Ca²⁺]_(i) elevation mediated by trypsin (FIG. 79a) or thrombin (data not shown). However, at 100 nM which fullyactivating EGFRs, EGF totally blocked the N-DMR event, but onlyattenuated the P-DMR event for the DMR responses mediated by trypsin(FIG. 79 b), or thrombin (FIG. 79 c). These results suggested that theremay be cross-communication between EGFR and PARs, at least in terms ofregulating the actin filament reorganization.

In summary, to elucidate the molecular mechanisms of PAR signaling inA431 cells, five PAR agonists (thrombin, PAR1-AP FLLLR-amide, trypsin,PAR2-APs GLIGLR-amide and GLIGKV-amide) and one PAR1 specific partialagonist YFLLRNP was used to stimulate A431 cells. The cellular responsesincluding changes in [Ca²⁺]_(i) level and dynamic mass redistributionwere examined. Three lines of evidence supported that thrombin primarilyactivates PAR1, while trypsin activates both PAR1 and PAR2. First, thedose-dependence and saturability of [Ca²⁺]_(i) elevation and DMR signalto either of PAR agonists examined suggested the presence of PAR1 andPAR2 signaling in A431 cells. Compared to those mediated by other PARagonists, the greater [Ca²⁺]_(i) elevation and DMR signals mediated bytrypsin suggested that trypsin might activate receptor(s) other thanPAR2. The [Ca²⁺]_(i) elevation mediated by a mixture of SFFLR-amide andGLIGKV-amide is similar to that mediated by trypsin alone, furtherstrengthening the possibility that trypsin activates both PAR1 and PAR2in A431 cells. The second evidence is from the observations that thepreceding stimulation with trypsin almost completely blocked the[Ca²⁺]_(i) elevation mediated by either one of all PAR agonists, but notbradykinin (a B₂ receptor agonist), thus suggesting that along withPAR2, PAR1 was cleaved and activated by trypsin. On the other hand, thepreceding stimulation with thrombin attenuated only slightly the[Ca²⁺]_(i) elevation, but significantly the DMR signal mediated bytrypsin. Interestingly, the prolonged preceding stimulation (˜1 hr) withtrypsin totally inhibited the DMR response of A431 cells mediated bythrombin, suggesting that no intact thrombin-activated receptor(s)recovers after one hour continuous stimulation with trypsin. However,unlike the [Ca²⁺]_(i) measurement, the prolonged preceding stimulationwith trypsin only partially suppressed the DMR signals mediated by allthree PAR-APs, implying that there might some portions of PAR2 receptorsbeing recovered. SFFLR-amide is known to be able to activate both PAR1and PAR2. It is also known that receptor proteolysis and phosphorylationregulate the activities of PARs through receptor internalization and theinhibition of intracellular signal transduction. Depending on thecellular context, the recovery of functional receptors at the cellsurface could take from tens of minutes to hours. The third line ofevidence came from the effect of YFFLRNP. The preceding stimulation withYFFLRNP dose-dependently suppressed the DMR signals mediated bythrombin, SFFLR-amide or trypsin, but not a PAR2-AP SLIGKV-amide. At thehighest dose (729 μM), YFFLRNP totally blocked the DMR signal mediatedby thrombin, but only partially suppressed those induced by SFFLR-amideor trypsin. Collectively, these results suggested that beside PAR2,trypsin might also activate PAR1 in A431 cells. It is reported thatPAR1, PAR3 and PAR4 serve as thrombin receptor, while trypsin is able toactivate PAR1 and PAR4, besides PAR2.

The actin filament staining with Texas Red-X-phalloidin, together withthe dynamic mass redistribution as manifested by the RWG biosensor,supported the roles of the activation of PAR1 and PAR2 in thecytoskeletal reorganization of A431 cells. The activation of PAR1 hasbeen shown to lead to cytoskeletal reorganization in several types ofcells including platelets and LNCaP cells. The stimulation of A431 cellswith either thrombin or trypsin triggered significant rearrangement ofactin filaments from the randomized distribution of elongated actinfilaments to concentrated filaments near the rim of the cells.Furthermore, all PAR agonists examined also induced dramatic massredistribution within the bottom portion of adherent cells on thesurface of the biosensors. The ability of actin filament disruptionagents latrunculin A and cytochalasin B, but not actinpolymerization-prompting agent phalloidin or microtubule disruptionagent nocodazole, to selectively attenuate the DMR signals mediated bythrombin or trypsin suggested the roles of actin filament rearrangementin the DMR responses, thus the roles of PAR signaling in thecytoskeletal reorganization in A431 cells. In human platelets, whichundergo extensive spreading and shape change when exposed to thrombin,PAR1 has been shown to activate RhoA through p115Rho-GEF, a GTP exchangefactor (GEF) that associates with the PAR1-coupled G-proteins,G_(12/13). In A431 cells, YFFLRNP, a PAR1 specific partial agonist thatis reported to specifically activate G_(12/13) but not G_(q), was foundto be able to induce a DMR signal similar to other PAR agonists (datanot shown). Furthermore, the pretreatment of A431 cells with YFFLRNPdose-dependently attenuated the DMR signals mediated by thrombin andSFFLR-amide, but not PAR2-AP GLIGKV-amide. These results suggested thatthe activation of PAR1 in A431 might also trigger the cytoskeletalreorganization through G_(12/13). On the other hand, thetrypsin-mediated cytoskeletal reorganization may be resulted from bothG_(12/13)- and G_(q)-dependent pathways, since the trypsin-mediated DMRsignal was sensitive to a CaMKII inhibitor KN-62 as well as the PAR1specific partial agonist YFFLRNP. One possibility is that trypsininduced the cytoskeletal reorganization depending on the G_(q) signalingpathway through the activation of PAR2, but the G_(12/13) signalingpathway through the activation of PAR1.

Together with other lipids including sphingolipids and saturatedphospholipids, cholesterol at the cell surface tends to assemblemicrodomains, which function to selectively compartmentalize numeroussignaling proteins. The treatment of cells with mβCD but not itsinactive stereoisomer αCD attenuated PAR signaling including Ca²⁺mobilization and dynamic mass redistribution induced by thrombin andtrypsin. The effect of the preceding stimulation with EGF suggested thatthe transactivation of EGFR by cholesterol depletion at least accountsfor the attenuation of the N-DMR event mediated by thrombin or trypsin.Furthermore, the ability of cholesterol depletion to attenuate the Ca²⁺mobilization implicated that cholesterol in the plasma membraneregulates the signaling of both PAR1 and PAR2 through G_(q)-signalingpathway. It is known that cholesterol extraction leads to the loss ofcompartmentalization of PtdIns 4,5-P₂, and G_(q), two importantmolecules for PAR signaling. The suppression of Ca²⁺ mobilization bycholesterol depletion might be a direct result of delocalization ofPtdIns and G_(q). As discussed above, the DMR signals mediated throughPARs may involve other pathways independently of G_(q) pathway. However,the ability of cholesterol removal to fully block the DMR signalmediated by trypsin and thrombin suggested that cholesterol depletionmight also impair other signaling pathways, such as G_(12/13). Thesefindings agreed with the previous observations done by others that themembrane raffling in A431 cells requires cholesterol. Interestingly, thefunctional recovery experiments showed that the cholesterol-assembledmicrodomains are dynamic and reversible.

The Ca²⁺ signaling and dynamic mass redistribution by trypsin, thrombin,or PAR-APs suggested that thrombin mediates PAR1 signaling, and trypsinactivates both PAR1 and PAR2 in A431 cells. The activation of both PAR1and PAR2 leads to the reorganization of cytoskeleton structure, butpossibly through distinct mechanisms. The G_(q) and Ca²⁺-dependentmechanism is assigned to the PAR2-mediated cytoskeletal rearrangement,while other signaling pathways including G_(12/13) might contribute tothe PAR1-mediated rearrangement. Furthermore, cholesterol at the cellsurface plays important roles in regulating the PAR signaling in A431.These findings suggest that PAR signaling might be important to tumorinvasion and metastasis. The present study strongly augments the greatpotentials of the RWG biosensors in deciphering the cell signaling andits network interaction.

10. Example 10 Study of Reactive Oxygen Species Signaling and Cell RedoxStates

ROS regulates a large number of signaling pathways at multiple levelsfrom receptor to nucleus. Cellular targets, although less clear, havebeen identified and broadened over the past decade. Receptor kinases andphosphatases may be targets of oxidative stress. Growth factor receptorsare most commonly activated by ligand-induced dimerization oroligomerization that autophosphorylates its cytoplasmic kinase domain.Ligand-independent clustering and activation of receptors in response toultraviolet light have also been well demonstrated, and this effectappears to be mediated by ROS. Exogenous H₂O₂ (usually in the millimolarrange) has been shown to induce tyrosine phosphorylation and activationof the PDGF- and EGF receptors. Lysophatidic acid-inducedtransactivation of the EGF receptor appears to be mediated by theintermediate formation of ROS. Because most growth factors and cytokinesappear to generate ROS at or near the plasma membrane, phospholipidmetabolites are potentially important targets for redox signaling. Forexample, the oxidized forms of diacylglycerol were more effective inactivating PKC than its nonoxidized forms. In addition, PKC activationand protein tyrosine phosphorylation appear to be required forH₂O₂-induced PLD activation in endothelial cells and fibroblasts.Non-RTKs belonging to the Src family (Src kinases) and Janus kinase(JAK) family are also targets, at least, for exogenously added oxidants.

In this study, all optical responses were monitored with a wavelengthinterrogation system. The RWG biosensor is comprised of three majorcomponents for bioassay applications: an Epic™ sensor microplate, an RWGdetector, and a liquid handling system. The sensor microplate consistsof a glass bottom plate attached to a plastic holy plate of a given SBSformat (e.g., 96-well or 384-well), which enables high throughputscreening. In a 96 well Epic™ sensor microplate, each well contains oneRWG sensor of approximately 3×3 mm². The RWG sensor consists of a thinfilm of dielectric material on the grating presenting glass substrate.

The wavelength interrogation detector system is centered on integratedfiber optics. A broadband light source, generated through a fiber opticand a collimating lens at nominally normal incidence through the bottomof the microplate, is used to illuminate a small region of the gratingsurface. A detection fiber for recording the reflected light is bundledwith the illumination fiber. A series of 8 illumination/detection headsare arranged in a linear fashion, so that reflection spectra arecollected from all 8 wells within the same column of a microplate atonce. With the spatial-controlled movement, the whole plate is movingacross the illumination/detection heads so that each sensor can beaddressed multiple times, and each column be addressed in sequence. Aseries of spectra of the reflected lights are collected and used foranalysis. Since this detection system measures the wavelength shift ofthe reflected lights induced by the cell response in response tostimulation, this approach is referred to the wavelength interrogationsystem.

FIG. 80 presented multi-optical output parameters of quiescent A431cells in response to 1 mM H₂O₂, as monitored by the angularinterrogation system. The stimulation by H₂O₂ triggered significant massredistribution within the sensing volume of the sensors (FIG. 84A). TheDMR signal consists of two major events: an initial peak that comprisesof three phases—an increased mass signal (P-DMR), a transition phase,and a decreased mass signal (N-DMR); and a prolonged and increased masssignal that ultimately leads to a plateau. On the other hand, thestimulation by H₂O₂ also slightly increased the PWHM of the resonantpeak of TM₀ mode, indicating the increased inhomogeneity of massdistribution within the bottom portion of cell layer. Consistent withthe PWHM, the peak intensity also slightly decreased over time after thestimulation, while the integrated area remained almost constant.

FIG. 81 showed the dynamic mass redistribution signal of quiescent A431cells in response to H₂O₂ at different doses, as monitored by the shiftin the wavelength with the wavelength interrogation system. As shown inFIGS. 81 a and b, the optical signatures of H₂O₂ stimulation dependstrongly on its doses. When the concentration of H₂O₂ is at or belowabout 8 mM, the cells respond to H₂O₂ with a typical curve that consistsof two major events: an initial peak and a prolonged increased masssignal. However, when the concentration of H₂O₂ is at or above 16 mM,the cells respond to H₂O₂ with distinct characteristics: an initialincreased mass signal followed by a somewhat steady transition state andultimately a decreased mass signal. The later decreased mass signal iswell consistent with the observations with Live/Dead cell staining (datanot shown), which indicated that the cells treated with high doses ofH₂O₂ undergo apoptosis—a process leading to the loss of cellular mass.

FIG. 82 showed the effect of src kinase modulators on the cell responsesmediated with 1 mM H₂O₂. Results showed that two specific src kinaseinhibitors, PP1 and PP2, significantly suppressed the H₂O₂-mediated cellresponses, whereas the negative control, PP3, did not affect theresponses. These suggested that Src kinase involves in the H₂O₂-mediatedDMR signal; and optical biosensors can be used to screen modulators thataffect ROS signaling.

FIG. 83 showed the effect of different redox states of quiescent A431cells on the H₂O₂-mediated DMR signal. The different redox states wereachieved by using different initial seeding numbers of cells incombination with different culturing time. The low redox cells wasachieved by culturing 75,000 cells per well for 3 days culturing undernormal conditions and subsequently overnight starvation with 0% fetalbovine serum (FBS), while the high redox cells was achieved by culturing10,000 cells per well for 10 days culturing under normal conditions andsubsequently overnight starvation with 0% FBS. The cell densities weresimilar (˜95%), as examined with light microscopy. As shown in FIG. 83,two different redox states of cells responded to 4 mM H₂O₂ differently.H₂O₂ triggered a typical DMR signal for the low redox state of cells,which ultimately increased the mass within the bottom portion of cells.However, H₂O₂ at the same concentration mediated a DMR signal of thehigh redox state of cells with a characteristic of cells undergoingapoptosis (i.e., ultimately lost in mass within the cells). Theseresults indicated that optical biosensors can be used to differentiatethe redox states of cultured cells, and to screen modulators that affectthe redox states of cells.

11. Example 11 Analysis of Multiple Optical Output Parameters for CellAssays

Multiple optical output parameters were recorded in real time and inparallel for several well-studied cell responses and processes,including adhesion and spreading, detachment, as well as signaling ofcells through EGFR or bradykinin B₂ receptor. These optical readoutsinclude the shift in the incident angle, as well as three parametersdefining the shape of the resonant peaks: intensity, PWHM and area.Because of its high sensitivity and information content, only TM₀ modewas used for all data collection and analysis.

a) The Shape of the TM₀ Peak

As shown in FIG. 31, the shape and position of the TM₀ peak for culturedCHO cells was found to be dependent on the cell confluency. As the cellconfluency increases, the resonant peak shifts towards the direction ofhigh incident angles. The PWHM value, a parameter defining the peakshape, also exhibited a dependence on the cell confluency (FIG. 31 b).The PWHM value reached its maximum at the cell confluency of about 50%;the maximum PWHM was about 35% higher than those in the absence orpresence of cell monolayer with high density above 75%. It is worthynoting that these data were obtained after cells became fully spreadafter ˜2 days culturing in a growth medium.

The TM₀ peak of adherent CHO cells was also found to be sensitive toDMSO a toxic compound when high doses are used. As shown in FIG. 32 a,the shape and position of the TM₀ peak exhibited dynamic changes whenproliferating cells, obtained in 10% FBS, was treated with 18% DMSO.After treated with DMSO, both the intensity and area of the peakincreases throughout the time monitored (about 3 hours). However, thepeak position (i.e., the incident angle) showed dynamic characteristics:the incident angle initially shifts towards an increase in mass (e.g.,25 min), and then a decrease in mass (e.g., 40 and 120 min). Similarly,the peak shape initially became broadened and showed a complicate finestructure (e.g., 25 min), and eventually became narrow (e.g., 40 and 120min). The appearance of complicate peak structures has been used as animplication of large-scale irregular inhomogeneity of mass at or nearthe sensor surface, thus indicating that during certain period aftertreatment with DMSO, the biosensor senses the increased surfaceinhomogeneity. The live/dead staining pattern of CHO cells, obtained 25min after the DMSO treatment, showed that there were mixed populationsof cells: viable, dead and affected cells (FIG. 32 b), implying that theCHO cells seem respond heterogeneously to the DMSO treatment. Theseresults suggested that the shape of the TM₀ peak is useful to examinethe heterogeneous lateral mass distribution within the sensing volume.

(b) Cell Adhesion and Spreading

The adhesion and spreading of cells at surfaces were well studied usingoptical imaging techniques, as well as optical biosensors such as SPRand RWG. Cells start to interact with a surface by initial contact orattachment where cells generally retain the round shape they possessedin suspension. Subsequently, attached cells undergo morphologicalchanges known as spreading—a process that the cells increase their areain contact with the surface. Both attachment and spreading are dependenton the nature of the surface and of the medium in which the cells aresuspended. Since cell adhesion and spreading obviously leads to bothvertical and horizontal mass redistribution within the sensing volume,we first characterized the adhesion and spreading of A431 cells in 5%FBS in the absence and presence of vincristine. Vincristine is a plantalkaloid that inhibits microtubule assembly by binding to tubulin.

We studied the adhesion and spreading of A431 cells in 5% FBS in theabsence and presence of vincristine at room temperature (25° C.).Results show that in the absence of vincristine, the shift in theincident angle exhibited three major phases (data not shown). Followingthe addition of cell solution, there is an immediate and rapid increasedsignal, which is probably resulted from three events: the increased bulkindex from the addition of the cell solution, the immobilization ofserum proteins onto the sensor surface, and the sedimentation of cellsand subsequent contact of cells with the surface. Afterwards, aprolonged increased signal occurred, indicating the slow process of cellspreading. Ultimately a saturated level was reached. The saturated level(16.8±0.6 unit, n=3) was much lower than those of fully spread cells atsimilar density (22.6±1.0 unit, n=3). On the other hand, the normalizedPWHM value was also found to be dynamic with distinct characteristics(data not shown). After the cell solution was added, the PWHM valuestarted to increase. About 20 min later, the PWHM began to decay back toits original level within about 2 hours, followed by a slowly continuousincrease until it reached a plateau. The PWHM at the endpoint was about25% higher than that at the starting point, which indicated that thecells were still not fully spread, even after 20 hours assaying with thebiosensor under ambient condition. This was confirmed by lightmicroscopy images (data not shown). These results suggested that (i) atroom temperature A431 cells seem not be able to reach optimal degree ofadhesion; (ii) the cells interact with the surface through multiplesteps, each has its own characteristics; and (iii) the spreading stepclearly increases the mass within the sensing volume, which meansincreased contact of the cell with the surface.

The presence of 100 nM vincristine significantly altered the opticalsignatures. The presence of vincristine suppressed not only both theinitial and total responses, but also reduced the kinetics of cellspreading (data not shown). The total change in the incident angle inthe presence of vincristine was about 20% less than that in the absenceof vincristine. Interestingly vincristine also altered the dynamicfeatures of the PWHM value (data not shown). Unlike in the absence ofvincristine, the PWHM initially decreased and remained low for about 3hours, and subsequently increased until it reached a plateau, indicatingthat vincristine primarily affects the initial steps during the celladhesion and spreading processes. These results suggested that thebiosensor is not only able to provide insights for the interaction ofcells with the surfaces, but also to differentiate compounds for theirability to alter cell adhesion and spreading processes.

(c) EGFR Signaling

As discussed above, rich information had been obtained through analysisof the modulation of the EGF-induced DMR signals by a variety of knownmodulators. Results showed that the DMR in quiescent A431 cells mediatedby EGF required EGFR tyrosine kinase activity, actin polymerization, anddynamin activity, and mainly proceed through MEK. The optical signaturesof EGFR signaling mediated by EGF using parallel multi-parametermeasurements were characterized. As shown in FIG. 84 a, the cellresponses, as manifested by the angular shift, induced by high doses ofEGF were particularly interesting. When stimulated with high doses ofEGF above 32 nM, a novel phase of DMR signal was observed for quiescentA431 cells. Besides an initial rapid P-DMR with increased signalfollowed by a short transition phase and a long decay N-DMR withdecreased signal, there is a partial recovery RP-DMR phase withincreased signal before the cells ultimately reaches a plateau whichexhibits similar level to those induced by either 16 nM or 32 nM. Onepossibility is that after stimulated with high doses of EGF the cellsunderwent a detachment process, followed by a partial re-attachmentprocess.

Since EGF mediates asymmetric lateral redistribution of certain cellulartargets such as PI3K that is important for EGF-induced cell migration,parameters defining the shape of the resonant peak were monitored inparallel. However, all three parameters seem to remain constant afterstimulated with EGF at different doses (FIG. 85 b; only the PWHM waspresented), indicating that EGF stimulation does not increaseinhomogeneity of lateral mass distribution within the bottom portion ofcells. This is contradictory to the staining pattern of actin filamentswith TR-phalloidin (FIGS. 85 c and d). These images showed that EGFmediated significant rearrangement of actin filaments in lateraldimensions. The inability to detect any inhomogeneity of lateral massredistribution triggered by EGF suggested that the asymmetricredistribution might mainly occur outside the sensing volume.

b) Bradykinin B₂ Receptor Signaling

Bradykinin B₂ receptor is a G protein-coupled receptor, and accounts formost of the physiological and pathophysiological action of bradykinin(BK). Bradykinin (BK) appears to act as a mediator of a wide variety ofphysiological and pathophysiological responses including mitogenic andanti-mitogenic effects. A431 cells endogenously express bradykinin B₂receptor, but not B₁ receptor. Disclosed herein the optical signaturesof quiescent A431 cells in response to BK stimulation werecharacterized, and it was found that A431 cells responded to BKstimulation with dynamic mass redistribution; its kinetics, amplitudesand duration depend on the cell culture conditions, the dose of BK, andthe cellular context. As showed in FIG. 86, BK stimulation of quiescentA431 cells results in a rapid increase in PWHM, followed by a slow decayback to the original level, while the peak intensity gave rise to adynamic response that is inverse to those of the PWHM and the angularshift. Furthermore, the changes in both parameters are also BKdose-dependent, and their dynamics and kinetics exhibited similarity tothe DMR signals previously reported. These results suggested thatcompared to EGF-mediated cell responses, BK stimulation leads to moresignificant asymmetric redistribution of cellular contents, which, inturn, increases the inhomogeneity of lateral mass distribution withinthe bottom portion of cells.

In summary, the RWG biosensors provided rich information content forprobing living cells. Theoretical analysis revealed that the opticalsignatures measured are integrated responses and can be used forreadouts for examining cells in their native environments without theneed of labels. Several cell responses and processes including adhesionand spreading, detachment and cell signaling through EGFR and bradykininB₂ receptor had been investigated systematically. Parallel and kineticmeasurements of multiple optical output parameters led to identificationof unique signatures for stimulation-mediated dynamic massredistribution in both vertical and lateral dimensions within the bottomportion of cells. Cell adhesion and spreading had been found to involvemultiple steps; vincristine was found to be able to modulate the celladhesion and spreading by interfering with its initial steps.Unexpectedly, EGF did not trigger obvious asymmetric lateral massredistribution, at least within the bottom portion of cells Thissuggested that the EGF-induced asymmetric distribution of cellularcontents, an important process for cell migration, occurs in the topportion of cells, rather than in the bottom portion of cells. However,increasing the penetration depth of the biosensor (such as reverseswaveguide configuration) should be able to allow one to detect suchlateral redistribution. Nonetheless, the multiparameter monitoringshould add more dimensions that allow one to distinguish the cellularevents induced by the stimulation.

Interestingly, the activation of B₂ receptor in A431 induced bybradykinin triggered both vertical and lateral mass redistribution.

12. Example 12 High Throughput Screening of Compounds Against EndogenousGPCRs Using Endpoint Measurements

Disclosed are methods that are suitable for high throughput screening ofcompounds that modulate or effect one or more signaling pathways in acell or cell proliferation or cell death. These high throughput methodsare based on the understanding that the biosensor output data can beassessed using a number of different parameters, as discussed herein.And that particular cells or particular receptors within cells orparticular cell events such as death or proliferation or modulation of asignaling pathway can have a particular signature, as discussed herein.This signature can be made up of one or more biosensor output parametersas discussed herein. Importantly for high throughput methods, it isimportant that the there be a time point during the method where thecollection of the biosensor output parameter data will be diagnostic ofthe state of the cell, i.e., a signaling pathway was activated ordeactivated or the cell has dies or the cell is proliferating. Thispoint can be where there is a combination of biosensor output parametersthat are used to define the signature.

The ligand-induced DMR signals typically proceed for a prolonged periodof time (˜tens of minutes). Thus kinetic measurements do not seemamenable for high throughput (HT) screening applications. However, basedon the overall dynamics and well-characterized kinetics of the DMRsignal induced by a particular ligand, one can readily develop endpointmeasurements for HTS applications. Based on the optical signature of twoGPCRs: bradykinin B₂ receptor in A431 cells, and protease activatedreceptor subtype 1 (PAR1) in CHO cells, two endpoint measurements wereused to develop high throughput screening methods.

FIG. 86 showed the wavelength shift between two time points during theassay as a function of compounds. The two time points were right beforethe compound addition (the baseline point), and 5 minutes after thecompound addition (the measured point). The difference between twoendpoints reflects the total amplitude of the P-DMR event mediated bybradykinin—a bradykinin B₂ receptor agonist. The B₂ receptor isendogenously expressed in A431 cells. The cells become quiescent beforethe bradykinin stimulation. In this example, a 384 well Coring Epicbiosensor plate was used. Each well contains A431 cells with aconfluency of ˜90%. Half of the wells were treated with bradykinin at100 nM, whereas other half of the wells were treated with the bufferHBSS only. Results showed that cells treated with 100 nM bradykininresult in a total change in wavelength of about 800 pm, where the cellstreated with HBSS buffer only respond with a much small amplitude (about−10 pm). The assay window is quite large (˜810 pm), and assay varabilityis small (˜6% in CV for the cells treated with bradykinin).

FIG. 87 showed the wavelength shift between two time points during theassay as a function of compounds. The two time points were right beforethe compound addition (the baseline point), and 5 minutes after thecompound addition (the measured point). The difference between twoendpoints reflects the total amplitude of the P-DMR event mediated bythrombin—a PAR1 receptor agonist. Here a different cell line —CHO cellswas used. The PAR1 receptor is endogenously expressed in CHO cells. Thecells become partially quiescent by culturing the cells in the DMEMmedium for 4 hours before the thrombin stimulation. In this example, a384 well Coring Epic biosensor plate was used. Each well contains CHOcells with a confluency of ˜90%. Half of the wells were treated withthrombin at 40 unit/ml, whereas other half of the wells were treatedwith the buffer HBSS only. Since the agonist-induced activation of bothB₂ in A431 and PAR1 in CHO cells leads to Gq signaling, the significanceof this assay results is that the Gq-type optical signature is at leastuniversal in both cell lines. By using similar endpoint measurements,one is able to screen GPCR modulators against different endogenoustargets in different cells.

FIG. 88 showed the wavelength shift between two time points during theassay as a function of thrombin concentration. The two time points wereright before the compound addition (the baseline point), and 5 minutesafter the compound addition (the measured point). The CHO cells weretreated with thrombin at different doses. Results showed that by usingthe endpoint measurements, the cells dose-dependently responded tothrombin stimulation, leading to an apparent EC₅₀ of 12.5 unit/ml. Thisassay results suggested that the endpoint measurements not only enablehigh throughput screening of GPCR modulators, but also enable thedetermination of agonism and the efficacies of GPCR agonists forendogeneous GPCRs in real physiological conditions. Unlike conventionalmethods which assay a discrete cell response or a particular labeledtarget, the biosensor-based cell assay is applicable to large-scale andmultiple target-based selection of potential ligands. Once a unique DMRsignature is identified and linked to a particular signaling pathwaythrough a specific class of target in a cell line at specific states, alibrary of compounds are screened. The compounds can be classified intodistinct categories based on their optical signatures. Such a screen isuseful for compound classification.

Alternatively, since a compound resulting in a given type of opticalsignature could be an agonist to a same class of endogenous receptorssuch as Gq-coupled receptors. The effect of preceding stimulation withsuch a compound on a receptor-specific agonist-induced DMR signal can beexamined and used as an indication of target specificity. Such a screenis useful for target-based screening.

The identification of an appropriate lead structure is a key step indrug discovery. Once a lead structure is selected, the action of it onliving cells can be studied systematically using the disclosed opticalbiosensors. For example, panels of well-known modulators of a set oftargets in signaling pathways can be used to study the modulationprofiles on the lead structure-induced DMR signal, thus linking theaction of the lead structure to a specific target or a signalingpathway. Once the linkage is established, biosensors can then be used tooptimize the lead structure. Since cell signaling through a target iscomplex, lead structures can be further optimized such that they onlyselectively modulate a specific oligomerization state of a receptor, ora specific pathway or a state of cells.

1.-258. (canceled)
 259. A method to test the effect of a stimulatoryevent on a cell comprising: providing a label-free biosensor; incubatinga cell on the biosensor; providing a stimulatory event to the incubatedcell; and collecting biosensor output from the biosensor.
 260. Themethod of claim 259, wherein a stimulatory effect is identified from thebiosensor output.
 261. The method of claim 259, wherein the stimulatoryevent affects cell viability, cell proliferation, or has an effect onabsorption, distribution, metabolism, excretion, or toxicity of thecell.
 262. The method of claim 259, wherein the stimulatory eventcomprises adding a compound to the cell culture and the compoundmodulates a cell signaling pathway.
 263. The method of claim 262,wherein the compound modulates a cell surface receptor on the cell. 264.The method of claim 263, wherein the cell surface receptor is a Gprotein-coupled receptor, an ion channel, a receptor tyrosine kinase, acytokine receptor, an integrin receptor, a Na+/H+ exchanger receptor, animmune receptor, a G_(q)-coupled receptor, a G_(s)-coupled receptor, aG_(i)-coupled receptor, a G_(12/13)-coupled receptor, epidermal growthfactor receptor (EGFR), platelet derived growth factor receptor (PDGFR),fibroblast growth factor receptor (FGF), or vascular endothelial growthfactor receptor (VEGFR), or combination thereof.
 265. The method ofclaim 259, wherein collecting biosensor output from the biosensorcomprises collecting a biosensor output parameter related to thekinetics of the biosensor output and analyzing the overall kinetics ofthe biosensor output comprising at least one of: analyzing the rate ofchange from one phase to another phase at the completion of a phasetransition; analyzing the length of time it takes to complete output ofthe biosensor output; analyzing the length of time for which an overallphase of the output of the biosensor output takes; analyzing the totalduration of a P-DMR phase; analyzing the total duration of an N-DMRphase; analyzing the rate for attaining the total amplitude of theP-DMR; analyzing the rate for attaining the total amplitude of theN-DMR; analyzing the rate to go from a N-DMR to a P-DMR; analyzing thetransition time t from a P-DMR phase to a N-DMR phase, a net-zero phaseto a P-DMR phase, a net-zero to a N-DMR phase, a P-DMR phase to anet-zero phase, or a N-DMR phase to a net zero phase; analyzing thephases of the biosensor output; or a combination thereof.
 266. Themethod of claim 265, wherein analyzing the phases comprises at least oneof: analyzing a phase transition; analyzing a Positive-Directional MassRedistribution (P-DMR) signal; analyzing a Negative-Directional MassRedistribution (N-DMR) signal; analyzing a net-zero Directional MassRedistribution (net-zero DMR); analyzing the shape of aPositive-Directional Mass Redistribution (P-DMR) signal; analyzing theamplitude of a Positive-Directional Mass Redistribution (P-DMR) signal;analyzing the shape of a Negative-Directional Mass Redistribution(N-DMR) signal; analyzing the amplitude of a Negative-Directional MassRedistribution (N-DMR) signal; analyzing the shape of the complete curveproduced by the biosensor output; or a combination thereof.
 267. Themethod of claim 259, wherein incubating the cell comprises culturing toa confluency of 20-99%.
 268. The method of claim 259, wherein thebiosensor output is at least one of: an optical waveguide lightmodespectra (OWLS); a resonant peak of a guided mode; or a resonant bandimage of a guided mode.
 269. The method of claim 259, wherein thebiosensor is embedded in the bottom of a microplate having a pluralityof wells, a different type of cell is cultured in each of two or morewells, the stimulatory event is provided to the two or more wells, thestimulatory event comprises adding a ligand to a receptor tyrosinekinase (RTK) to the two or more wells, the biosensor output is collectedfrom the two of more wells, and the biosensor output is thetime-dependent response of the different types of cell.
 270. The methodof claim 259, wherein the cell has a relatively high expression level ofa receptor tyrosine kinase (RTK), the biosensor is embedded in thebottom of a microplate having a plurality of wells, a cell is culturedin each of two or more wells, a stimulatory event is provided to the twoor more wells, the stimulatory event comprises adding a ligand to theRTK to the two or more wells, a different concentration of the ligand tothe RTK is added to the two or more cells, the biosensor output iscollected from the two of more wells, and the biosensor output is thedose- and time-dependent response of the cells in the different wells.271. The method of claim 259, further comprising detecting a label witha device capable of detecting the label.
 272. The method of claim 271,wherein the label is a fluorescent label, a radioactive label, or aphosphorescent label.
 273. The method of claim 271, wherein the step ofdetecting the label occurs simultaneously with collecting label-freebiosensor output.
 274. The method of claim 259, wherein a plurality oflabel-free biosensors are provided, a cell is cultured on each of two ormore of the biosensors, the stimulatory event is provided to the two ormore biosensors, and the biosensor output is collected from the two ormore biosensors.
 275. The method of claim 259, wherein the biosensor hasa first region having no material-containing mixture deposited, and asecond region having a material-containing mixture deposited such thatwhen the cell is incubated on the biosensor the cells on the secondregion become transfected by the materials.
 276. The method of claim259, wherein the biosensor comprises two or more biosensors that areeach physically separated with a barrier, the barrier defines acompartment within the well that is lower than the barrier defining thewell in the microplate.
 277. The method of claim 259, wherein theincubated cell has a receptor tyrosine kinase (RTK), the incubated cellis suspended in a medium containing serum at a concentration that allowsfor the attachment and growth of the cell on the biosensor surface, andthe incubated cell adheres to the biosensor surface.
 278. A method ofidentifying a state of a cell, the method comprising: culturing the cellon a surface of a label free-biosensor to form a cell-biosensorcomposition; and assaying the cell-biosensor composition, where theassaying comprises identifying an inhomogeneity of the surface where thecell is cultured.
 279. The method of claim 278, wherein assaying thecell-biosensor composition differentiates between at least one of: anarea of the biosensor surface in contact with a viable cell; an area ofthe biosensor surface in contact with a cell that has been affected by astimulatory event; an area of the biosensor surface contacting no cell;or a combination thereof.
 280. The method of claim 279, wherein thereare multiple biosensors in a single well of a microplate, and themultiple biosensors are physically separated with or without a barrier.281. The method of claim 280, wherein the biosensors are physicallyseparated with a barrier, the barrier that defines a compartment withinthe well is lower than the barrier defining the well in the microplate.282. A method of determining a state of a living cell comprisingobserving the dynamic mass redistribution of the cellular contents witha resonant waveguide grating biosensor.
 283. A method for testing acompound's effect on a cell comprising: culturing cells on a biosensor;washing the cells; starving the cells; incubating the compound with thecell; and recording a signal with a biosensor.